• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The purpose of the present invention is to provide a valve state monitoring system which can be easily retrofitted to various existing or operating valves (rotating valves), actuators, and particularly even to a facility not being supplied with commercial power supply, and with which it is possible to perform detailed and accurate state monitoring, diagnosis, or failure prediction of the valves and actuators. The valve state monitoring system performs state monitoring, diagnosis, and lifetime prediction with respect to a valve on the basis of angular velocity data of a valve shaft for opening and closing the valve. A monitoring unit including at least a semiconductor-type gyro sensor is detachably attached to the valve shaft. The angular velocity data include angular velocity data, obtained from the monitoring unit, corresponding to rotating motion of a valve body from being fully open or fully closed to fully closed or fully open.
    公开号:ES2813248A2
    申请号:ES202090061
    申请日:2019-06-06
    公开日:2021-03-22
    发明作者:Yu Inoue；Masahiro Kazama；Isao Nishizawa
    申请人:Kitz Corp；
    IPC主号:
    专利说明:

    [0001] Valve Status Capture Method and Valve Status Capture System
    [0003] Technical field
    [0005] The present invention relates to valve state capture methods and a valve state capture system, and in particular to a state capture method and a state capture system for a rotary valve such as a valve. ball.
    [0007] Background of the technique
    [0009] Generally, in various locations, including large facilities such as various plants and buildings or small facilities such as houses and shops, various plumbing facilities, including various pipes and valves, and furthermore, various actuators are provided for automatic control. of these valves. In these plumbing installations, for example, between rotary valves such as ball valves and butterfly valves, those of the 90 degree rotation type (quarter turn type) are highly demanded. Also, as actuators to drive these, pneumatic actuators are often fitted, which are simple in structure, easily reduced in size, and are also of excellent cost.
    [0011] Normally, in these plumbing installations, for automatic control of devices and the like such as valves and actuators and management and maintenance of the operating situation, means are required to monitor the status of these devices and the like by means of some mechanical means. or artificial. Furthermore, in recent years, the scarcity of qualified human resources and the scarcity of technological heritage are becoming more conspicuous. There has also been an increasing demand not only for status monitoring for valves and actuators in plumbing installations, but also for prediction of failure and diagnosis of the life of these devices and, what is more, more accurate detection capacity at the product level and / or component, and systems capable of managing and controlling the devices based on those detection results from various points of view.
    [0013] In particular, a rotary valve of a type such as a ball valve (particularly a floating type) or a butterfly valve that includes a valve seat made of Resin such as PTFE or PEEK material and which rotates upon successively receiving the complicated and fine action of friction under a driving force by an actuator has been used as a typical open / close valve or flow adjustment valve in any of several ways. of use in many environments regardless of area or location, and in recent years its means of diagnosis and precise condition monitoring have been increasingly in demand. For example, a ball seat of a ball valve is the core of the valve function and an area that tends to change its state due to material characteristics and has the highest need to capture the state in the ball valve in operation. .
    [0015] On the other hand, as means for the purpose of at least monitoring the status of a valve and / or an actuator in plumbing installations, various techniques have conventionally been suggested. For example in PTL 1, on the basis of a graph of acquired characteristic of the operation of a device, especially, the valve and / or the actuator, an attempt is made to compare various states of the device. PTL 1 describes a method for determining the status of a process configuration control component by using characteristic charts, and specifically the method in which a measurement for a characteristic chart is performed by a device for a predetermined period, and then a measurement for a characteristic graph is performed by the same device during another period, and these two characteristic graphs are displayed on a monitor by means of a calculating device, thereby the status of the device is evaluated on the monitoring device. calculation by comparing feature graphs (if state is between boundary values).
    [0017] On the other hand, in various plumbing installations as described above, regardless of the structure and the situation, artificial means may be required for a worker, that is, an on-site check of the operating situation of the actuator and / or the valve, due to various causes. For example, in a simple plant structure without a sophisticated instrumentation system such as a featured bus, a control room or the like cannot perform remote monitoring and control, and thus a worker has to show up at that site to check on one. in one individual valves and actuators. Also, even if a remote monitoring system is provided, if it is out of order or the like, at least one site check is required.
    [0019] However, in this on-site check, for example, even if a predetermined flag or something similar is provided to the control tree of a Valve actuator, if the valve or actuator is installed in complex duct or narrow place and this plumbing situation is not supported, on-site check work is difficult. In addition, a facility configured to be remotely monitorable is often configured, with system simplification, as one where on-site testing is not assumed. Also in this case, an on-site check is difficult. Furthermore, when recent attempts have been made to provide a recording and display device to an existing actuator or valve to promote an on-site check, work is often required to disassemble, connect, or replace devices such as the actuator, valve, and plumbing. Additionally, if such a device is provided, the actuator or the like can be increased in size and may not even be arranged in the conduit.
    [0021] For this reason, in site check work around plumbing fixtures as described above, the condition of the valve and / or actuator can be easily checked on site. Also to a valve and / or actuator that has been arranged in the plumbing installations or is working, recently, monitoring means configured as a type of unit have been highly demanded to be retrofittable with ease. Furthermore, in recent years, a system configuration that can manage devices such as valves by means of technology called IOT (Internet of Things) and / or cloud computing technology has also been desired. Still further, there is a demand for a system that has an existing instrumentation system but can capture the status of a device in a simple way independently of that existing system. Several suggestions for such techniques are already present and, for example, those for PTL 2 and 3 have been suggested.
    [0023] PTL 2 describes a predictable maintenance system for valves, specifically, the system configured to be such that, while a magnetic type position sensor is accommodated in a box attachable and detachable to a support member on a housing side, magnets that generate , each, a magnetic field to be measured by a sensor is arranged on a stem side with predetermined spacing and a state such as a damage to a ball or seat or a failure of an actuator is declared based on at least one position Angle of the stem acquired from an angle sensing mechanism formed from these and torque information from a torque sensor included in the stem and, in particular, the state is evaluated from a par-angle curve graph.
    [0024] PTL 3 describes an example configured to be such that, while a supplemental valve type monitoring unit is connected by means of a bracket to a top of an actuator mounted on a quarter turn valve, a sensor capable of reading an actuator state (angular position of a stem) and transmitting an angular variation signal to the monitoring unit is connected on the stem side of a valve, thereby allowing the valve status to always be monitored on the basis of the angular position of the stem. For example, in a graph diagram of that PTL, a graph of stem angles versus time is plotted and based on its pattern, a defective valve condition is inferred.
    [0026] Appointment list
    [0028] Patent bibliography
    [0030] PTL 1: Japanese Patent Application Pending Examination Publication (PCT Application Translation) No. 2009-543194
    [0032] PTL 2: WO 2016/139376
    [0034] PTL 3: Japanese Patent Application Pending Examination Publication (PCT Application Translation) No. 2015-528085
    [0036] Summary of the invention
    [0038] Technical problem
    [0040] However, while the technique in PTL 1 can be considered as being broadly applicable for general purposes in view of comparison and evaluation of the graphical characteristics of the device, specific means such as a method for acquiring graphs of characteristics are not described. Thus, for example, it is impossible to carry out precise detection and diagnosis of the status of individual specific targets for each type of valve such as a ball valve or a butterfly valve or for each component such as a valve seat or gasket, and it is more , in relation to a damage state, substitution timing, etc. of these. Thus, it cannot be said that the art can perform the precise condition acquisition and diagnosis described above for each specific target such as a ball valve or butterfly valve.
    [0042] In this sense, although they are specifically described as examples of the characteristics graphs, it is a graph of the actuator pressure and movement position of a pneumatic actuator, to acquire this characteristic graph of an actuator existing, that is, after a plumbing connection, it is required to remove at once a plumbing system that admits and expels air pressure, have a pressure sensor or something similar to be incorporated into the actuator, and then assemble the actuator again. Thus, easy retrofitting as a monitoring device to a device or the like is impossible.
    [0044] Also in the device configuration of the PTLs 2 and 3, a separate connection of a member as a measured target to at least one valve or actuator side such as a stem is a requirement. Thus, the devices of the PTL 2 and 3 are of an external information measurement type and, since this measured member is required, the number of device components and the manufacturing and management steps are increased, time and effort is required. for connection to alter the manageability and, furthermore, the application objective is limited and the usability is diminished. It can be said that these are disadvantages. Thus, the techniques in PTL 2 and 3 are still insufficient in view of the problems described above to achieve a simple structure and easy retrofitting.
    [0046] Furthermore, in PTLs 2 and 3, the status of the device is merely captured on the basis of data from the angle sensor that detects the angle of the rotating shaft such as a stem. However, as will be further described later, in order to grasp in detail the motion of especially the rotating shaft rotating as it receives the random action of friction with a simple structure in detail, the sensor formed from at least the angle sensor is still insufficient to achieve detailed motion analysis and, in particular, it is insufficient as a data acquisition means for use in life diagnosis. Specifically, in the angle sensor, only a smoothly curved or linear graph can be acquired as temporary angle transitions. This means that, in the angle sensor, only insufficient coarse motion data is acquired with low precision. Thus, it is impossible to solve the problems described above to achieve more accurate target status acquisition and diagnosis when using angle information by the angle sensor.
    [0047] In fact, in the angle-time graph described in PTL 3, each graph of real-time measurement values assumes a linear shape or a smooth curve, and thus it can be said that only an approximate rotational motion characteristic is captured. In particular, while measuring graphs vibrating as waves are depicted, these are merely examples where the valve rotation is reversed and merely an extremely rare and simply over-oscillating motion is captured.
    [0048] Additionally, for the problems described above, at least for valve and / or actuator status monitoring, it is required, as expected, to provide a sensor capable of measuring these conditions (such as angular rotation). In particular, a sensor that can be easily retrofitted is considered effective. Various such techniques have been conventionally suggested, for example, with an inertial sensor (Inertial Measurement Unit (IMU)) provided to a valve and / or actuator, but have merely been suggested merely as valve opening gauges that measure a degree of opening (angular rotation) of a valve. Thus, even if the valve and / or the actuator is provided with a sensor, such as an inertial sensor, which can be easily retrofitted to a product target, it is not possible to know such data has to be acquired from this sensor, why how and how the acquired data is used to solve the problems described above (accurate status capture and diagnosis) etc., and thus it is impossible to solve the problems described above.
    [0050] Thus, the present invention was developed to solve the problems described above, and is intended to provide a valve status sensing system that can be easily retrofitted to any of a number of existing or operating valves (rotary valves) and actuators, and , in particular, even installations that are not supplied with commercial power, and allows detailed and accurate capture and diagnosis of status or prediction of failure for the valve or actuator.
    [0051] Solution to the problem
    [0053] To achieve the object described above, the invention according to claim 1 is directed to a valve status capture system configured to perform, based on angular velocity data of a valve stem that opens and closes a valve, status monitoring, diagnosis and life prediction of this valve.
    [0054] The invention according to claim 2 is directed to the valve status sensing system in which the database has stored therein a table of reference data formed from a plurality of pieces of tag data and the trait data according to a predetermined count of valve openings / closings for each specific condition, the sensor unit and / or the server are provided with first fault diagnosis means configured to capture the state of wear and perform a valve fault diagnosis, and these first anomaly diagnosis means include specific data generation means that generates specific data formed of a specific condition of the valve, a count of valve openings / closings, and specific feature data based on angular velocity data, media data acquisition systems that acquire from the reference data table reference data having an open / close count equal to the open / close count of the specific data and a substantially equal specific feature value, and means of comparison and determination comparing any piece of tag data included in this acquired reference data and a predetermined threshold to acquire a predetermined determination result.
    [0056] The invention according to claim 3 is directed to the valve status capture system in which the database has stored in it a learning model that calculates a piece of label data inferred from the trait data, the unit of sensor and / or the server are provided with second fault diagnosis means configured to capture the state of wear and perform a valve fault diagnosis, and these second fault diagnosis means include feature value generation means that generate the trait data based on the measurement data, inferred tag data calculation means that computes a piece of inferred tag data by means of the learning model based on the trait data, and comparison and determination means that they compare this inferred tag data and a predetermined threshold to acquire a determination result.
    [0058] The invention according to claim 4 is directed to the valve status capture system in which the database has stored therein a learning model that calculates accumulated trait data model data, the sensor unit and / or The server is provided with third anomaly diagnosis means configured to capture the state of wear and perform an anomaly diagnosis of the valve, and these third anomaly diagnosis means include feature value generation means that generate predetermined feature data based on the measurement data, data accumulation means that accumulates the trait data in the database and generates the accumulated trait data, data control means that perform predetermined control, model data calculation means that calculate the model data by means of the learning model based on the accumulated trait data, index calculation means calculating a predetermined index swimming the model data and new trait data, and comparing and determining means comparing the index and a predetermined threshold to acquire a determination result.
    [0059] The invention according to claim 5 is directed to the valve status sensing system in which the wear component is a valve seat, the valve is a rotary valve, the sensor unit is a single unit capable of wireless communication with the server and including a power supply, and this sensor unit is attached pluggable and detachable in a mode capable of simultaneous rotation with the valve stem.
    [0061] The invention according to claim 6 is directed to the valve condition sensing system in which the label data is formed from dimensional data formed of a dimension of the wear component in a wear-free state and / or leakage quantity data formed of a leak amount when the valve is fully closed.
    [0063] The invention according to claim 7 is directed to a valve status capture system that includes a valve, a gyro sensor unit attached to this valve, and a server communicatively connected to this gyro sensor unit and that includes a database , wherein, this database has stored in it a second reference data table that includes output data and product data according to a count of openings / closings of the valve, the sensor unit and / or the server. provide fourth fault diagnosis means configured to detect a state of wear of a wear component included in the valve and perform a fault diagnosis of the valve, these fourth fault diagnosis means include data generation means that generate data measurement including output data and product data measured by the gyro sensor unit based on a valve open / close count, media d e data acquisition acquiring, from the second reference data table, second reference data having output data substantially equal to the valve output data included in this measurement data, and failure determination means determining Valve failure prediction based on valve usage frequency data included in these second acquired baseline data.
    [0065] Advantageous effects of the invention
    [0067] According to the invention, the valve stem of the valve is a part together with the valve body and directly receiving its movement, and thus it is suitable as part for observing the movement of the valve body at which the performance and symptom of the valve at the present time is directly reflected, such as the state of the valve seat through friction action. Also, since the valve stem is directly related to various important parts such as the support and packing, the states of these also tend to be directly reflected.
    [0069] On the other hand, essentially, unlike positional (angular) data, velocity (angular) data with at least high precision indicates information at which of the movement characteristics of a target at the moment of measurement are reflected well and For example, in random motion under the action of friction, an unreflected fine motion characteristic is also reflected on the position data. Thus, if the valve stem angular velocity data is taken as a basis, it is possible to easily and accurately achieve condition monitoring, diagnosis and prediction of valve life.
    [0071] Furthermore, according to the invention, according to the gyro sensor, the rotational motion (rolling friction) can be acquired as an angular velocity graph having a non-linear region including a plurality of peaks. Thus, detailed diagnostic information that has been difficult to capture can be acquired in a simple way, allowing the status of the valve to be captured in detail on the basis of this data. Also, since the gyro sensor is a sensor for detecting rotary movement with respect to the reference axis with high precision, the gyro sensor is very useful as a sensor for life prediction even if it is a cheap, low-performance or high-purpose sensor. general.
    [0073] Also, in an actual use phase, with substantially only the work of detachably attaching the monitoring unit to the valve stem portion of each product target, a simple valve status capture system independent of the product can be configured. existing system. Also, the width of the connection target (such as product type, plumbing situation, and operation is being performed) and the connection method is very wide. Thus, any worker can very easily retrofit the system to any of a variety of product targets. What's more, the functions can be compactly concentrated as a monitoring unit, manageability or usability as a product is excellent, also in view of cost, etc.
    [0075] Furthermore, according to the invention, since at least the rotary shaft of the rotary valve is taken as the measurement target, the movement target to be measured by the gyro sensor is formed solely of a simple axial rotary movement with respect to the non-reference axis. displaced, and thus the gyro sensor's function as an axial rotation motion sensor can be fully exerted. Therefore, accurate motion measurement can be performed with a simple structure.
    [0076] Furthermore, according to the invention, it is possible to capture the status of a quarter-turn ball valve or butterfly valve, which has been widely spread in various scenes regardless of whether the valve is of the manual or automatic type and is currently highly demanded or it will also be in the future for various needs. Also, when performing angle calculation of acquired angular velocity data, among others, of valve movement, the accumulation interval (angular displacement) is small, 90 degrees at maximum. Thus, accumulated errors can only be in a small interval, which can also lead to a saving of computing resources and the structure of the device.
    [0078] Furthermore, according to the invention, the valve seat, the stuffing box, and / or the stem bearing each assume a significant part of the valve, and the performance of these, including the state of wear, influence the important functions of the valve. valve. On the other hand, these are internally built-in consumable members, and thus the wear condition of these is normally subjected to removal / disassembly of the valve device, component removal, and visual inspection and it is difficult to at least grasp the wear condition quickly of simple and non-destructive way. However, according to the present invention, detailed diagnosis can also be achieved with extreme ease for these interior components and important parts associated with the life of the product.
    [0080] Furthermore, according to the invention, the information about the angle and the opening degree is important as basic information about the valve in various scenes, and the angular velocity data can be used effectively at least for angle calculation.
    [0082] Furthermore, according to the invention, the wear state of the valve wear component is diagnosed on the basis of the trait value of the acquired measurement data of actual valve operation. Thus, anomaly diagnosis by means of a so-called non-destructive inspection scheme to capture the state of the device from a drive signal. This is but to allow rational replacement in view of the maintenance of the whole system in a plumbing system where a plurality of valves are arranged in a single plumbing. That is, even if maintenance is performed on only one valve, the operation of its plumbing has to be stopped, and all replacement is done under present circumstances even if there is another valve arranged that is still usable. According to the present invention, since a valve with less frequency of use has a longer practical life expectancy than that of other valves of the same type and therefore it is not required to be replaced, cost reduction in relation to maintenance can be achieved. Also, since data is kept for the entire period from the moment when the product is new to a moment when the product fails, even if the gyro sensor is connected to a valve whose period of use lasts up to a certain point, the state of use. Thus, predictive failure control can be developed rapidly on the market.
    [0084] Furthermore, according to the invention, the rotary movement of the valve stem has a very strong tendency to be characterized by a graph of angular velocity acquired by measurement by the gyro sensor, and thus the processing of the measurement data is also performed very easily. The invention is very suitable for capturing the target state also in view of a large amount of data processing such as, in particular, machine learning.
    [0086] Furthermore, according to the invention, the trait value is restricted to have only any one of several recognizable graph patterns, and thus it is possible to extract trait data that is easy to process.
    [0088] Furthermore, according to the invention, on the basis of the clear pattern acquired from the angular velocity data, the valve can be easily diagnosed from the reference table by means of simple processing. Also, the acquired reference data of actual operation of the valve product can be used very effectively. What's more, default machine learning can also be applied.
    [0090] Furthermore, according to the invention, by using a machine learning scheme with unique data specialized for the purpose, a valve abnormality diagnosis is performed based on the tag data acquired by means of this machine learning. Thus, with the development of machine learning technology in recent years, an improvement in the performance of calculators and data storage capacity, and a decrease in cost, it is possible to easily perform an anomaly diagnosis with specialized precision for the purpose. and high reliability.
    [0092] Furthermore, according to the invention, it is possible to carry out a diagnosis based on real-time data according to the individuality of the product in actual operation being used under specific conditions. Thus, the accuracy and reliability of the diagnosis can be improved depending on the product and, at least when configuring the system, it is only necessary to prepare a database only for an individual product that actually works.
    [0093] Furthermore, according to the invention, since the sensor unit is a single unit capable of wireless communication, retrofitting and removal from the facilities where the valve or valve status monitoring is arranged is very easy, and the unit itself is also easy. to handle.
    [0095] Furthermore, according to the invention, a value that is important for valve characteristics is selected as tag data, and thus the invention is very suitable for abnormal valve diagnosis.
    [0097] Furthermore, according to the invention, when all the data from a state in which the valve is new to a state in which the valve has failed is stored in advance in the second reference data table, by the failure determination means determining valve failure prediction based on the valve usage frequency data, a notification of a replacement timing can be done momentarily in a staggered manner, such as three months before or three months before. What's more, since data is kept for the entire period from the moment when the product is new to a moment when the product fails, even if the gyro sensor is connected to a valve whose period of use lasts up to a certain point, it can be captured the state of use. Thus, predictive failure control can be developed rapidly on the market.
    [0099] Brief description of the drawings
    [0101] Figure 1 is an external perspective view of a ball valve equipped with an actuator of the present example.
    [0103] Figure 2 is an external plan view of Figure 1.
    [0105] Figure 3 is a sectional view of a part along a line A-A in Figure 2.
    [0107] Figure 4 is a block diagram showing an interior structure of a monitoring unit of the present example.
    [0109] Figure 5 is an example of a graph of angular velocity acquired in one embodiment (test number 10) under specific conditions.
    [0111] Figure 6 is an example of the graph of angular velocity acquired in the embodiment (test number 10) under specific conditions.
    [0113] Figure 7 is an example of the graph of angular velocity acquired in the embodiment (test number 10) under specific conditions.
    [0114] Figure 8 is an example of the graph of angular velocity acquired in the embodiment (test number 10) under specific conditions.
    [0116] Figure 9 is an example of the graph of angular velocity acquired in the embodiment (test number 10) under specific conditions.
    [0118] Figure 10 is a sectional view of a line B-B of Figure 3, the sectional view represents an example of a ball valve in a fully closed state.
    [0120] Figure 11 is a sectional view of the line B-B of Figure 3, the sectional view represents an example of the ball valve with a degree of opening in the middle.
    [0122] Figure 12 is a sectional view of the line B-B of Figure 3, the sectional view represents an example of the ball valve with one degree of opening in the middle.
    [0124] Figure 13 is a sectional view of the line B-B of Figure 3, the sectional view represents an example of the ball valve with one degree of opening in the middle.
    [0126] Figure 14 is a sectional view on the line B-B of Figure 3, the sectional view represents an example of the ball valve in a fully open state.
    [0128] Figure 15 is an example of a graph of angular velocity acquired in one embodiment (test number 2) under specific conditions.
    [0130] Figure 16 is an example of the graph of angular velocity acquired in the embodiment (test number 2) under specific conditions.
    [0132] Figure 17 is an example of the angular velocity graph acquired in the embodiment (test number 2) under specific conditions.
    [0134] Figure 18 is an example of a graph of angular velocity acquired in one embodiment (test number 8) under specific conditions.
    [0136] Figure 19 is an example of the graph of angular velocity acquired in the embodiment (test number 8) under specific conditions.
    [0138] Figure 20 is an example of the graph of angular velocity acquired in the embodiment (test number 8) under specific conditions.
    [0139] Figure 21 is an example of a graph of angular velocity acquired in one embodiment (test number 11) under specific conditions.
    [0141] Figure 22 is an example of the graph of angular velocity acquired in the embodiment (test number 11) under specific conditions.
    [0143] Figure 23 is an example of the graph of angular velocity acquired in the embodiment (test number 11) under specific conditions.
    [0145] Figure 24 is a schematic descriptive diagram describing an example of a situation for measuring a wear amount of a ball seat.
    [0147] Figure 25 is an example of an X-axis angular velocity graph acquired in another example (initial motion).
    [0149] Figure 26 is an example of a Y-axis angular velocity graph acquired in the other example (initial motion).
    [0151] Figure 27 is an example of a Z-axis angular velocity graph acquired in the other example (initial motion).
    [0153] Figure 28 is an example of an X-axis angular velocity graph acquired in another example (twenty thousand times).
    [0155] Figure 29 is an example of a Y-axis angular velocity graph acquired in the other example (twenty thousand times).
    [0157] Figure 30 is an example of a Z-axis angular velocity graph acquired in the other example (twenty thousand times).
    [0159] Figure 31 is a block diagram depicting a general sketch of a valve status sensing system of the present invention.
    [0161] FIG. 32 is a flow chart depicting a general outline of an abnormality diagnosis process of the valve status pickup system of the present invention.
    [0163] FIG. 33 is a data flow diagram depicting an abnormality diagnosis process (normal flow) by fourth abnormality diagnosis means.
    [0165] FIG. 34 is a data flow diagram showing an anomaly diagnosis process (reference creation flow) by the fourth anomaly diagnosis means.
    [0166] Figure 35 is an example of an acceleration graph acquired in another example (initial motion).
    [0168] Figure 36 is an example of an acceleration graph acquired in another example (twenty thousand times).
    [0170] Description of achievements
    [0172] Next, the valve status sensing system in an embodiment of the present invention is described in detail on the basis of the drawings. Figure 1 is an external perspective view of an actuator equipped ball valve in a state in which a monitoring unit 1 is connected to an actuator 2 in the present embodiment, and Figure 2 is an external plan view of the actuator 2 in Figure 1 from above. Also, Figure 1 represents a fully open state of a valve 3, with the X axis coinciding with a central axial flow path direction, the Y axis is in a direction (upward direction in the drawing) in which a shaft Control 4 extends out with respect to this X axis, and the Z axis is a clockwise rotation direction on the X and Y axes.
    [0174] In Figure 1 and Figure 2, as for a housing (accommodation means) of a monitoring unit 1, any outer shape, material and others can be selected as long as the housing has a compact size and weight to the extent of being easily portable with one hand. In the present example, the housing is a resin-made housing formed in the shape of a rectangular plate having a length of approximately 15 cmx10 cm and a thickness of approximately 3 cm and having a weight of the order of several hundred grams as a finished product. . For example, one side of the front surface displays product information, model number, or connection address (method of use), etc. On a rear surface side, a predetermined connecting part formed of a female screw hole, a cohesion surface, etc. is provided. not shown, which allows a coupling 5 to be connected thereto. Alternatively, for example, the housing may be formed into a circular disc shape of roughly similar size.
    [0176] Coupling 5 is an example of a connecting means, and in the present example, it is formed of an L-shaped metal plate, with a side surface serving as a connecting surface fixedly connected to the rear surface side of the connecting unit. monitoring 1 and the other surface side fixedly connected to an upper end of the control shaft 4 of the actuator 2 with a bolt 6. Here, the NAMUR standard is an interface standard (VDI / VDE 3845-2010) for actuators, and The dimensions for the valve connection and connection of an accessory are defined in a top of the actuator. If the actuator 2 meets this NAMUR standard, an upper end portion of the control shaft 4 is provided with a female screw portion, not shown, that meets this standard. By using this female part, the monitoring unit 1 can be easily retrofitted to the actuator 2 by means of the coupling 5.
    [0178] Here, in an actuator that is already in use, an accessory device such as an open / close travel limit can be connected to an upper part of the control shaft 4. In this case, by using the metal plate in the form of L of the present example, the monitoring unit 1 can be connected to the control shaft 4 while securing an upper space of the control shaft 4 with the accessory device connected thereto.
    [0180] In Figure 1, Figure 2 and Figure 4, a gyro sensor 7, which is a rectangular semiconductor element incorporated in the monitoring unit 1 of the present example, is provided to an inner substrate to be parallel to the short sides and the long sides of the rectangular monitoring unit 1. Specifically, in Figure 1 and Figure 2, the monitoring unit 1 is connected to have an orientation parallel to the XY plane. In this state, the orientation axis of the gyro sensor 7 coincides with the Z-axis direction and the roll axis and the pitch axis coincide with the Y-axis and X-axis directions, respectively.
    [0182] In Figure 2, in the present example, in a reference position where the valve 3 is in a fully open state, the gyro sensor 7 incorporated in the monitoring unit 1 is provided to be double positioned eccentrically with respect to the position of the control shaft 4. Specifically, the monitoring unit 1 is arranged in a position remote in parallel from the axial center position of the control shaft 4 (central axial direction of the flow paths 26a and 27a), an eccentric distance to (direction to the right in the drawing) by means of the coupling 5 and, depending on the position of the gyro sensor 7 on the substrate, it is arranged in a position away from the central axial position of the bolt 6 (vertical direction to the axial center of the flow paths 26a and 27a an eccentric distance b (downward direction in the drawing) In the present example, a = 18mm and b = 33mm are set.
    [0184] With the gyro sensor 7 arranged in this doubly eccentric position, at least when the monitoring unit 1 is connected to a product target, a vacant space where no other member is present can be easily used, and the monitoring unit 1 can be easily attached to the product lens in a compact way, and can also be easily retrofitted at the site to any of products with various sizes, structures and orientations. In particular, a coarse connection workability is favorable, and the width of connection targets is also widened. Also, while the position of the monitoring unit 1 is kept closed in distance to the position of the control shaft 4, a large rotation radius (a2 + b2) 1/2 can be ensured from the control shaft 4, which it is a rotating shaft as a measurement target. Note that the gyro sensor arrangement is not limited to the structure by means of the coupling 5, and can be fixed in a position midway of the control shaft in the axial direction by a coupling fixed in an adapter form to the control shaft. .
    [0186] In this way, the monitoring unit 1 having at least the semiconductor type gyro sensor 7 is attached to the valve stem in a connectable and detachable manner. Also, as will be further described later, in the present invention, based on speed data angle of the valve stem that opens and closes valve 3, status monitoring, diagnosis and life prediction of this valve is carried out. This angular velocity data includes data (Figure 5 to Figure 9, Figure 15 to Figure 23) formed in a graph of angular velocity according to a rotational movement of the valve body (ball 30) from being fully open or fully closed to fully closed. or fully open acquired from the monitoring unit 1. Furthermore, while the monitoring unit 1 is connected to the control shaft 4 in the present example, it can be connected to an output shaft 14 by means of appropriate connection means.
    [0188] In Figure 4, an example of a basic structure incorporated in the monitoring unit 1 is represented as a block diagram. This structure is not restrictive, and any structure can be selected depending on the implementation. However, the unit has at least 7 gyro sensor (angular speed sensor) as a motion sensor. The gyroscopic sensor 7 of the present example is a vibratory gyro sensor with MEMS technology (Micro Electrical Mechanical System) type IC, and it is of the semiconductor type and included in the interior substrate.
    [0190] Specifically, the gyro sensor is a triaxial gyro sensor capable of measuring rotation in orthogonal directions on three XYZ axes, and a built-in one is currently used in various general consumer products. More specifically, a "L3GD20" product manufactured by STMicroelectronics is used, and its characteristics are, for example: power supply voltage: 3.3 V DC (operating range: 2.4 V DC to 3.6 V DC); current consumed: 6.1 mA; Measurement range: ± 250 dps (resolving power: 0.00875 dps), ± 500 dps (resolving power: 0.0175 dps), and ± 2000 dps (resolving power: 0.07 dps). However, these features are not restrictive, and it goes without saying that any selection and adjustment can be made depending on the implementation.
    [0192] Additionally, in Figure 4, the monitoring unit 1 includes at least a CPU 8 (central processing unit), a memory 9, a communication module 10, a power supply 11 and an IC tag 12, and also includes a temperature sensor in the present embodiment described further below. Furthermore, in addition to the gyro sensor 7 described above, an acceleration sensor and a magnetic sensor not shown can be combined for use in the system of the present invention. Also, to save energy, a piezo sensor can be combined to activate the gyro sensor when needed.
    [0194] It is understood that the CPU 8 includes a cache, one with general specifications can be used, and any can be selected depending on the implementation. In particular, it is required to have processing capacity that can achieve each function further described below (in particular, power saving function). This CPU 8 is connected to peripheral elements such as memory 9 and communication module 10 by means of a bus. As with CPU 8, any memory 9 having capabilities (capacity and speed) capable of accomplishing each function further described below is also selected according to implementation. If no successive power supply is assumed, non-volatile memory is preferable. What's more, the ability to sufficiently read various applications that perform the function of power saving, etc. is adequate.
    [0196] Communication module 10 is desirably a near field wireless communication module. In the present example, Bluetooth (registered trademark) is used. By means of this communication module 10, at least the angular velocity data and its transition by the gyroscopic sensor 7 are communicated with an external portable terminal not shown. This portable terminal allows status recording and exposure checking of an automatic valve through a dedicated application. In addition, something other than Bluetooth (registered trademark), infrared rays, Wi-Fi Direct, or something similar can also be used.
    [0198] The power supply 11 includes a predetermined power supply conversion circuit, and any can be selected according to the implementation. For example, the power supply is an independent power supply by a button battery, or a battery power supply. For example, in the case of a button battery, in its connection and disconnection position, a battery cover in disc shape engages and is fixed to an orifice portion formed in a cap body by means of a sealing member not shown, and is provided in an attachable and detachable manner as it is rotated by a flat screwdriver or the like at an angle. predetermined. The power supply 11 has connected to it each of the elements, including the gyro sensor 7, the CPU 8, the memory 9 and the communication module 10, and serves as a drive source for these.
    [0199] On IC label 12, unique information about actuator 2 and / or valve 3 is accumulated. That information includes at least (1) the model type and order number of actuator 2 and / or valve 3 and (2 ) a URL to download application software. These chunks of accumulated information are fed into a dedicated terminal or the like not shown. The URL to download application software is for handheld terminals. From this URL to download, you can purchase application software.
    [0200] The monitoring unit 1 described above has at least, as part of a status monitoring and a function for capturing for the product target (valve 3 and / or actuator 2), a function for data measurement and a function for accumulating measurement data. Data from a measurement target includes angular velocity data in control shaft 4 for at least each or every count of openings / closings. The acquired data is taken from the gyro sensor 7, and accumulated in the memory 9 by means of data processing in the CPU 8. In this case, the data can be converted into data that can be exploited as a graph on an external monitor. Also, these chunks of data can be set to accumulate in memory 9 after performing at least simple data processing, such as so-called "interpolation" in which these chunks of data are accumulated in memory 9 from CPU 8 at constant intervals, an average data value, or default filtering (noise removal). In response to a request from the portable terminal, the accumulated data is transmitted to the portable terminal via the near field wireless communication module 10, which is Bluetooth (registered trademark). Using this portable terminal, recordings of the status of actuator 2 and / or valve 3 are displayed and checked.
    [0202] Also, as further described below, based on the monitored and sensed state of the valve, the monitoring unit 1 can include various functions required in a process (flow formed from various process steps) to perform symptom diagnosis, such as such as valve part / component level failure prediction (product target), optional functions such as power saving function and a function for data reading test by a auxiliary sensor (such as an acceleration sensor), or a function to be performed by a predetermined externally acquired application.
    [0204] Also, these various functions can be performed on the monitoring unit 1 or on an external server or the like, and are appropriately assigned as needed. In particular, when the structure is such that angle data can be further calculated on the basis of the angular velocity data, it is suitable to use an acceleration sensor as appropriate for drift correction of the gyro sensor 7 according to a summation calculation (such as as the rectangular method) by the four fundamental operations without intervention of integrating means, in view of data precision, power consumption, and load. What's more, on an external server or something similar, a default database can be built for use in data analysis from monitoring unit 1.
    [0206] In the present invention, basically, an angular velocity graph is acquired from the measured angular velocity data and, based on the shape / pattern analysis of these graph data, various diagnostic processes are performed including a prediction process of lifetime. These diagnostic processes include, for example, a process for recognizing and evaluating the chart pattern, a process for calling up existing accumulated data (chart data for comparison) for comparison with the acquired chart pattern, a symptom determination process. , and a process to extract and display the result, an alert, etc. A physical or logical system is configured so that these various processes can be performed appropriately.
    [0208] What's more, a function can be provided to measure and retain various unique data, a function to extract and externally expose these chunks of data, or a function to use in any of the processes described above, the various unique data includes, as unique information product target: fluid pressure, viscosity, and temperature; temperature and humidity of a product environment; valve open / close count and run time after installation; actuator supply pressure and actuation speed; or, in a ball valve, the material and wear coefficient of the ball seat or packing and the size of the ball and the flow path.
    [0210] In particular, the gyro sensor 7 has a large amount of electrical power consumption, and the monitoring unit 1 of the present invention is used as if a long period of time was left at a level of several years at the longest. Thus, in view of energy saving, it is important to select a combination of gyro sensor 7 and power supply 11, and the function for energy saving as well. It is important. For example, the CPU 8 may normally be in a power saving state to receive data from the gyro sensor 7 but not accumulate these data chunks in the memory 9 and, when the operation of the actuator 2 is detected, the power saving state. Energy can be erased and at least angular velocity data detected by gyro sensor 7 can be accumulated in memory 9. The state can be after the energy saving state after the state in which the actuator operation has not been detected 2 continues for a predetermined time. Note that, as a power saving function, for example, a gyro sensor of the self-generation type (such as vibration power generation or photovoltaic power generation) can be used.
    [0212] On the other hand, from Figure 1 to Figure 3, in the present example, as objectives of monitoring products for the monitoring unit 1, the pneumatic rotary actuator 2 is described in a double-acting scotch yoke structure and the 90 90 degree rotary ball valve 3.
    [0214] From Figure 1 to Figure 3, within the main body of the actuator 2 a conversion mechanism 13 is provided which converts a reciprocating movement to a rotational movement. The rotational force of this conversion mechanism 13 can be drawn by the output shaft 14 to a stem 15 of the ball valve 3. The conversion mechanism 13 is formed of a structure in which a scotch yoke 35 for transmission to the shaft rotary (valve stem) and with this scotch yoke 35 matched pin rollers 16 are provided to a piston stem 17, and these are incorporated in a housing 18.
    [0216] On one side of the housing 18, which is a right side in Figure 3, a cylinder part 19 is fixed. Inside a cylinder casing 20 of this cylinder part 19, a piston 21 integrated with the piston rod is accommodated. 17. Cylinder housing 20 may be coated with a material, for example, PTFE (polytetrafluoroethylene), ENP (chemical reduction nickel plating), or Hcr (hard chrome metallization). The present example describes a type of double actuation, and the cylinder part 19 is provided with air intake / exhaust ports 38 and 39. According to compressed air intake / exhaust to air chambers 22a and 22b by means of these air ports air intake / exhaust 38 and 39, the piston 21 reciprocates, and the piston rod 17 reciprocates linearly accordingly. This movement is transmitted to the scotch yoke 35 via the pin rollers 16 for conversion to a rotary movement.
    [0217] The scotch yoke 35 is provided with a rotating shaft to be inserted and extracted by means of a fixed connection part 23 which is provided to be able to fit on a knoll not shown. The rotation of the rotary shaft is transmitted by means of the fixed connection part 23 to the scotch yoke 35.
    [0219] The rotary shaft of the present example is formed from the output shaft 14 on one side of the ball valve 3 (lower side in Figure 3) and the control shaft 4 on its opposite side (upper side in Figure 3). The output shaft 14 and the control shaft 4 are inserted by means of cylindrical members 24 and 25 to the housing 18, respectively. In the cylindrical members 24 and 25, a predetermined bearing is fitted within a stem bearing made of metal not shown, these cylindrical members 24 and 25 are each fitted into a bearing portion formed in the housing 18, and the shaft of output 14 and control shaft 4 are inserted inside. The rotating shaft is rotatably and pivotally connected to the main body of the actuator 2.
    [0221] Note that according to implementation, actuator 2 may be provided with a pressure sensor (not shown) as appropriate. In this case, for example, a speed controller (not shown) is provided to each of the air intake / exhaust ports 38 and 39 and, between these air intake / exhaust ports 38 and 39, and to the controller speed sensor is connected to a pressure sensor by means of a coupling such as a T-tube, adapter tube, or the like. If so, with the pressure sensor inserted into a branch part of the T-tube, compressed air intake / exhaust is not affected, and the pressure measurement by a pressure sensor can be done with a simple structure.
    [0223] The target of state acquisition by the system of the present invention is a valve and, in the present invention, a rotary valve that opens and closes a flow path by rotating the valve stem. The valve stem is formed from the output shaft 14 and the control shaft 4 of an automatic valve by means of the actuator 2. However, the target valve stem is not limited to one of the automatic valve and, although not shown , it can be a rotary shaft formed from a stem of a manual valve by means of a manual handle. Also, while the rotary valve of the present example is a quarter-turn ball valve, the target can be any of a number of rotary valves, including motor-driven types such as a plug valve, butterfly valve, or a poppet valve. ball of a 180 degree rotary type.
    [0225] The ball valve 3 of Figure 1 to Figure 3 is a floating type ball valve, and a valve box is configured with a body 26 having a primary flow path. 26a and a body cap 27 having a secondary flow path 27a fixedly connected with bolts / nuts 28. On each of the body 26 and the body cap 27, a flange is formed at a connection portion of the flow path 26a , 27a.
    [0227] Ball 30, which is a valve body, is of a full bore type having a substantially spherical portion and a through path 30a formed to have the same diameter as those of flow paths 26a and 27a, and is supported by two annular ball seats A1 and A2, which are valve seats, from a primary side and a secondary side in the valve chamber. The clamping of the ball 30 by these ball seats A1 and A2 is adjusted by the clamping of the bolts / nuts 28. At an upper end part of the ball 30, a coupling part 29 is formed (for example, coupling part convex-concave) with which the stem 15 (valve stem) can be engaged. By means of this coupling part 29, a rotational movement of the ball 30 is transmitted with high precision to the stem 15.
    [0229] The stem 15 is rotatably connected to a gland part 31 of the body 26 by means of a cylindrical stem bearing B. Also, between the stem 15 and the gland part 31, a gland C and a packing washer are snap fit by a packing retainer 32. The fastening of the packing retainer 32 is adjusted by the fastening of a retaining bolt 33. A bracket 34, which is a coupling member between the main body of the actuator 2 and the ball valve 3, it is fixed with bolts 40. Also, in a lower part of the output shaft 14, a rectangular connecting part not shown is formed. To this connection part, a non-shown and formed interlocking part is fitted in an upper part of the stem 15 to couple the output shaft 14 and the stem 15, thereby transmitting a rotational movement of the shaft with high precision. outlet 14 to stem 15.
    [0231] In Figure 1, a rotary encoder 37 indicated by dotted lines is connected in advance to the product target prior to status monitoring by the system of the present invention to acquire data necessary for use in the present invention and basically does not it is supposed to be used in an actual use scene of the present invention. The encoder 37 in the drawing is connected to an upper end portion of the control shaft 4 by means of a substantially C-shaped connecting plate 36 to accurately measure at least one rotational speed of the control shaft 4, and the data of measurement is maintained as appropriate as unique product target data. In the present example, a product "E6C3-C" manufactured by OMRON Corporation is used.
    [0232] Next, a basic method of use in the valve condition monitoring system of the present invention is described. The monitoring unit 1 can be connected as appropriate to a location where the product target (valve or actuator) can be easily positioned, for example, it is connected to a location where the unit can be left undisturbed for a long period of time product target actuation. Although the connection mode depicted in Figure 1 and Figure 2 described above is not restrictive, it is required to connect the unit at least in a way to rotate simultaneously precisely with the rotation of the control shaft 4 (valve stem).
    [0234] When the unit is fixed in the mode depicted in Figure 1 and Figure 2, a bolt hole of the coupling 5 is matched with the female screw portion provided at the upper end of the control shaft 4 in the NAMUR standard and, With the state of the coupling 5 oriented to a proper fixing direction, only screwing in the bolt 6 can fix the unit. Thus, the monitoring unit 1 of the present invention can be easily retrofitted to a predetermined position of the product target without removing the existing actuator 2 and / or valve 3 from plumbing equipment or removing the actuator 2 from valve 3 or without adjusting not at all the existing instrumentation system or something like that. After positioning in this way, the rotational movement characteristics of the control shaft 4 can be accurately captured.
    [0236] Also, the connection mode described above reduces external prominence to prevent expansion of an installation space. Thus, the unit can also be connected to an automatic valve installed in a narrow space. The monitoring unit 1 can also be placed in a 180 degree offset position with respect to the actuator 2, and in this case, it can be positioned only by connecting and disconnecting the bolt 6 in a similar way as above. This allows the monitoring unit 1 to be provided on either opposite side 180 degrees, depending on the installation situation of the valve 3 and / or the actuator 2.
    [0238] Moreover, not only when the valve is in a fully open state but also even when this valve 3 is in a middle opening degree and the control shaft 4 is in the course of rotation, the monitoring unit 1 is switched on to this control shaft 4 as it is positioned as appropriate. Thus, even while the automatic valve is operating, the unit can be precisely connected to allow initial set-up work.
    [0240] After connection of the monitoring unit 1, the operating situation of valve 3 at each location can be visually recognized by using the terminal laptop. At this time, with the use of the Bluetooth communication module 10 (registered trademark), even if the valve 3 and / or the actuator 2 are installed in a complex duct or a narrow place, without visually recognizing these directly, the terminal laptop can do a check from a nearby place.
    [0241] When a function for initial setting mode is adopted in advance, to perform initial setting work performed on the handheld terminal immediately after the installation of the monitoring unit 1, it is only required to reset to the state of initial setting mode according to appropriate according to the mode of use of the monitoring unit 1. In this case, for example, data such as angle data are set to an initial value according to a fully closed state of the valve 3. Also at this time, no requires adjustment work on a product target side such as actuator 2 and / or valve 3, and establishment can be done by using, for example, product information and / or order number retained on the IC 12 label Also, for example, application software for handheld terminals is downloaded from the URL to download and initial setup data is transmitted to the server, allowing thereby recording an installation date of monitoring unit 1.
    [0243] After finishing the initial setting work, this initial setting mode is switched to a normal mode. As described above, at the time of switching to the normal mode, the power supply 11 can be set to an off state after a lapse of a predetermined time to transition to a power saving mode.
    [0245] On the other hand, as the portable terminal described above, for example, a smartphone, a tablet or the like not shown is used. In this case, as functions in relation to data inputs, the portable terminal has, for example, (1) a function for receiving data and information unique to the monitoring unit 1, (2) a function for transmitting the data and information single received from the monitoring unit 1 to the server (not shown), and (3) a function to retain GPS (Global Positioning System) position information, camera images, etc. and transmit them to the server.
    [0247] In (1) the function for receiving data and unique information from the monitoring unit 1, the angular velocity data at the moment of rotation of the control shaft 4 is received by means of the communication module 10. On the other hand, the information Only one of the actuator 2 and / or the valve 3 is received by means of the IC label 12.
    [0248] In (2) the function for transmitting the data and unique information received from the monitoring unit 1 to the server, for example, a midfield wireless communication module such as LTE ( Long Term Evolution) or Wi-Fi not shown is used, and transmission is made to the server from any of these. In this case, the measurement data is not processed.
    [0250] (3) The function to retain GPS position information, camera images, etc. and transferring it to the server is an optional feature. In this function, an image taken by the camera of the portable terminal and indicating the status of the actuator 2 is transmitted to the server.
    [0252] On the other hand, as functions in relation to data outputs when using the portable terminal, the portable terminal has, for example, (1) a function to cause the information received from the server to be exposed on the basis of the data transmitted to the server. and (2) a function for causing the information to be displayed, such as a preliminary anomaly report determined by application software on the basis of the information received from the monitoring unit 1 but not by means of the server.
    [0253] Although not shown, in (1) the function to cause the information received from the server to be displayed based on the data transmitted to the server, information including at least diagnostic results of the valve and / or actuator can be displayed in a visually recognizable shape with ease. For example, with angular velocity data displayed on a graph based on measured valve open / close count, in a range from fully open to fully closed (fully closed to fully open), along with comparison target data, and then the determination results are displayed. Also, it is possible to display each of the following: actuation count, operation time, pressure data and actuation torque history, fluid pressure and temperature, ambient temperature and humidity of the actuator 2 and, furthermore, drawings of the actuator actuator 2, valve 3, etc.
    [0255] Also, like other functions, maintenance recommendation information can be displayed based on the history described above, etc., or when it is suspected that a wrong entry in the initial setting of the monitoring unit 1 or the product target with the monitoring unit 1 connected thereto is an imitation, an indication can be displayed as such. Examples of this case are such that the actuation time of actuator 2 is extremely fast or slow for the type of model and the order number (special specifications vary for each order) of actuator 2 and / or valve 3 input to the IC tag 12, or the image of the actuator 2 at the site taken by the camera of the portable terminal is small.
    [0257] On the other hand, as (2) function of causing information to be exposed, such as a preliminary anomaly report determined by application software on the basis of the information received from the device but not through the server, for example, when the time drive is extremely long or when the value of the gyro sensor 7 is not changed even though an air pressure is applied, that is, when the actuator 2 is not activated, a determination is made as an abnormality, and it is exposed as a preliminary report. Furthermore, when this type of outlier is measured, an indication is also displayed to encourage the transmission of data to the server.
    [0259] Next, as a server for use in the system described above, the system has (1) a function to accumulate unique information from actuator 2 and / or valve 3, (2) a function to accumulate angular velocity data measurement data and air pressure of actuator 2, (3) a function for calculating actuator torque 2, and (4) a function for transmission and reception to the portable terminal.
    [0261] As (1) the function for accumulating unique information of actuator 2 and / or valve 3, the server accumulates drawing information and design information of actuator 2 for use in driving torque calculation. As (2) the function to accumulate measurement data of angular velocity and air pressure data of the actuator 2, when measurement data is received from the portable terminal in a plurality of times, the server accumulates these measurement data pieces as series . As (3) the function for calculating driving torque of the actuator 2, for example, based on the air pressure data received from the portable terminal of the cylinder diameter of the actuator 2, the displaced amount of the central axis of a pinion (or scotch yoke), conversion efficiency, etc. not represented. As (4) the function for transmission and reception to the portable terminal, transmission and reception are performed by a midfield wireless communication module such as LTE or wifi.
    [0263] Note that while the example has been described in the above embodiment in which an air pressure type actuator is used as the actuator for automatic operation, a fluid pressure type actuator other than air pressure type may be used, or it may be used a motorized actuator. The housing of the coupling 5 and the monitoring unit 1 can be changed according to the size of the valve 3 and / or the actuator 2 to suit its external shape. Furthermore, while in the above embodiment the control shaft 4 is provided according to the NAMUR standard, it can be provided according to another standard. Also in this case, training is done according to the shape, allowing that way connection to the actuator with easy retrofit, as with the NAMUR standard housing.
    [0265] Here, examples described further below are those in which a ball seat is diagnosed in a 90 degree rotation float valve. However, the system of the present invention is not limited to this objective, and detailed diagnoses can be made at the level of a specific symptom of part / specific of the product objective by analyzing the shape and pattern of a characteristic graph (graph angular velocity) generated from data that includes angular velocity data collected extensively from the product lens. In particular, in a valve, as a part / component target, it is suitable to include wear pickup of at least the valve seat, the packing gland and / or the stem bearing.
    [0267] Also, as depicted in Figure 5 through Figure 9 and Figure 15 through Figure 23, which are angular velocity graphs of the examples, at least a plurality of peak values are indicated on each angular velocity graph. This type of time course or degree of opening graph having these peak values cannot be acquired from, for example, a normal angle (position) sensor provided to a rotary valve. Thus, in conventional techniques, the system as in the present invention to make a detailed diagnosis based on the information about these peak values (such as positions, values, and peak width on the graph) cannot be configured. According to diligent studies by the applicant of the present application, it has been revealed that this type of angular velocity graph can be acquired from at least the gyro sensor 7, as described above.
    [0269] This is considered as follows, at least in a vibratory type gyro sensor of a semiconductor type made by MEMS, of its measurement principle. That is, since a normal angle sensor can only pick up one discrete angle for each duration, computing as a gradient in a duration on a time course graph is the only way to convert angle data to angular velocity. On the other hand, in the gyro sensor, an instantaneous Coriolis force felt by a vibrating element is converted to an angular velocity for measurement. Thus, depending on the setting, a substantially true angular velocity can be accurately measured. Also, in order to achieve this with an angle sensor, it is required to at least set an extremely small duration, and this is not practical.
    [0270] In this sense, for smooth, slow and continuous movements, there is not much difference between the two (data of angular velocity acquired from the angle sensor and that of the gyro sensor). However, for rotational movements of a target that makes movements such as receiving the action of fine, random and discontinuous friction, for example, the valve stem of a rotary valve, there is a difference between the two. Specifically, in a graph of angular velocity acquired from the angle sensor, fine movements cannot be tracked in detail, and therefore an unbent vibratory pattern, such as peaks, cannot be acquired. However, the gyro sensor can pick up fine movements of the valve stem well by the action of friction. Thus, the possibility exists that a precise angular velocity graph has been acquired with the appearance of peaks at a plurality of points.
    [0272] Furthermore, inertial sensors, which typify internal information type sensors, are normally classified into acceleration sensor and gyroscopic sensors. In conventional technologies, there are also valve opening gauges of a type that include this acceleration sensor and are readily provided to a top end portion of the rotary valve stem. That is, the angular rotation or the like of the valve handle is detected by means of this acceleration sensor or the like. However, while at least one MEMS-type acceleration sensor that has been used frequently in recent years is excellent, in principle, at detecting a translational motion or vibratory motion or a gradient with respect to the direction of gravity, Detailed detection of a rotational movement is not impossible but there is much room for improvement in detection with a simple structure.
    [0274] The acceleration sensor of this type has a property in which a movement in a horizontal plane without a gradient with respect to the direction of gravity is almost in a dead band and the detection of this type of movement is extremely difficult. What's more, the acceleration sensor easily picks up an unnecessary component other than rolling acceleration, such as gravity acceleration components and translational (vibratory) acceleration components. Also, it has been found theoretically that properly separating the measured unnecessary acceleration from an output signal is impossible when using at least one acceleration sensor. In practice, such a valve opening meter has a limitation in plumbing orientation and direction of a connection target and, in most cases, after confirming in advance the plumbing orientation of a valve as a connection target. , the sensor settings are adjusted for use according to that goal. Thus, it is difficult to catch a rotational motion rotating as random friction is received in detail even with at least a simple structure formed of only one acceleration sensor. Note that Figure 31 and Figure 32 described further below represent actual verification where no they can capture in detail data in relation to a rotational movement of a rotary valve, depending on the acceleration sensor.
    [0276] As specifically described in the following examples, the unique structure for the product target (ball valve) with the monitoring unit connected to it is associated with the positions, sizes and peak width of a plurality of peaks present in data. angular velocity but in graph form as appropriate to perform accurate status capture and accurate diagnosis of the product target based on those captured details.
    [0278] Examples
    [0280] Figure 5 through Figure 23 each represent an implementation example when the valve state is captured based on angular velocity data. Figure 5 to Figure 9 and Figure 15 to Figure 20 are examples of a graph of angular velocity acquired from the gyro sensor 7 by using the monitoring unit 1 of the present invention when the ball 30 is rotated 90 degrees from be fully closed to fully open in the quarter turn actuator 2 and the floating ball valve 3 depicted in Figure 1 to Figure 3 described above, with the angular velocity indicated on the right vertical axis (units: degrees / seconds) . Also, these angular velocity measurement values indicate measurement values in the Y-axis direction in the gyro sensor 7 depicted in Figure 1. Note that while the measurement values in the X-axis direction and the Z-axis direction They are not used as graph data in the present example, they can be used in a complementary way for the purpose of correcting a gyro sensor connection error.
    [0282] The lateral axis in each drawing indicates a valve actuation time, and it is time after supplying an air pressure to the actuator 2 by means of a speed controller (units: milliseconds). Specifically, the valve is a ball valve made of stainless steel that has a nominal diameter of 50 A and a nominal pressure of 20 K. Diagnostic targets are the ball seats made of PTFE + PFA A1 and A2, the stem bearing made of PTFE impregnated with fiberglass B, and packing C, which is a V packing made of PTFE (ball seats A, stem bearing B, and gland C are collectively referred to as "components of wear"). Also, as an opening / closing count shown in the drawings indicates, Figure 5 represents data acquired after opening / closing at zero time, Figure 6 after thirty times, Figure 7 after five hundred times, Figure 8 after one thousand times, and Figure 9 after ten thousand times. Also, Figure 15 and Figure 18 represent data acquired opening / closing at time zero, Figure 16 and Figure 19 after five hundred times, and Figure 17 and Figure 20 after fifteen hundred times.
    [0284] Furthermore, in the present examples, the encoder 37 as represented in Figure 1 together with the monitoring unit 1 is connected to the control shaft 4, and angle data acquired by this encoder 37 is also indicated on the left vertical axis. in each drawing as valve opening degree from Figure 5 to Figure 9 and from Figure 15 to Figure 20 (units: degrees).
    [0286] From Figure 10 to Figure 14 schematically represent full opening to full closing of the valve represented from Figure 5 to Figure 9 and Figure 15 to Figure 20 in this order of figure numbers and, specifically, are drawings to describe the positional relationship between the through path 30a of the ball 30 and the ball seats A1 and A2, etc. Figure 10 represents an opening degree of 0 (fully closed), Figure 11 represents an opening degree of approximately ten degrees, Figure 12 represents an opening degree of approximately twenty degrees, Figure 13 represents an opening degree of approximately eighty degrees, and Figure 14 represents a ninety degree opening degree (fully open). Note that Figure 10 to Figure 14 each correspond to a sectional view of line B-B in Figure 3.
    [0288] Also, when the state in Figure 10 is taken as 100%, a contact ratio between ball 30 and ball seat A is still 100% in Figure 11, it is decreased to 85% in Figure 12, are further decreased to 62% in Figure 13, and returned to 100% again in Figure 14.
    [0290] [Table 1]
    [0293]
    [0296] Ten test conditions in Table 1 are examples of test product conditions required as a minimum in view of quality engineering to examine the system of the present invention. From Figure 5 to Figure 9 represent data from experiments under the conditions of test number 10 in the table (however, the nominal pressure of the valve for use was 10 K), from Figure 15 to Figure 17 represent Data from experiments under test number 2 conditions, and Figure 18 to Figure 20 represent data from experiments under test number 8 conditions in the table.
    [0298] In Table 1, the drive time is a set time of a speed controller to drive a 90 degree rotation of the valve from fully closed to fully open, and the connection orientation is the orientation of the valve with respect to plumbing, in which horizontal indicates an orientation in Figure 1 with a bottom side in the drawing taken as floor, vertical indicates an orientation in Figure 2 with a bottom side in the drawing taken as floor, side indicates a plumbing orientation with the axial center of the flow path in Figure 1 rotated 90 degrees about the axis of rotation. Also, Action Supply Pressure indicates an air pressure (MPa) to be supplied to the actuator, and Fluid indicates type of test fluid. Fluid pressure indicates fluid pressure, plumbing bracket indicates a distance (cm) from the valve flange position to a part to support plumbing connected to the valve, and ambient temperature indicates temperatures of a test environment. Also, tests with test numbers 1 through 9 are performed in a bathtub at constant temperature and constant humidity, and a test with test number 10 is performed indoors.
    [0300] Next, using each of the angular velocity graphs from Figure 5 to Figure 9 (test number 10), from Figure 15 to Figure 17 (test number 2), and Figure 18 to Figure 20 (test number 8), with reference to the degree of opening valve situations depicted from Figure 10 to Figure 14, a general outline of the process for performing valve status monitoring is described. In this process, attention is directed to capturing, in particular, a state of wear of the ball seats A, as a valve state. Note that the diagnostic process as described below can be physically and logically entered into the monitoring system. the present invention after specifically implementing as information processing (a set of processing steps) capable of using computer hardware resources.
    [0302] Also, the prediction of valve failure and the prediction of life using angular velocity data by the system of the present invention can be captured from a rotational movement of the valve from being fully open or fully closed to fully closed or fully open in relation with the valve opening degree described above, that is, from angular velocity data transitions according to the entire entire valve strokes, or from angular velocity data transitions according to a part of the strokes, by example, regions of degree of valve opening that are characteristic such as regions T 1 to T 3 as further described below. What is more, as other data usable in the system of the present invention, for example, the operating state of the valve in a plant or building facilities or angular velocity data in a state of checking the operation of the valve can be used. (called a partial career test).
    [0304] First, from Figure 5 to Figure 9 (test number 10), region T 1 is a region in which the valve opening degree by encoder measurement is from a fully closed state to an opening degree of about 10 grades. The operation of the ball 30 corresponds to the states of Figure 10 to Figure 11.
    [0305] Within this region T 1 (a region in which the angular velocity frequently rises and falls in a state in which the ball 30 makes a contact seal with the entire circumference of each of the ball seats A1 and A2 ), the ball seats A1 and A2 are both in a state of being in contact with the ball 30, and this state corresponds to a state immediately after a transition from static friction to dynamic friction. As for the frequency of decrease in angular velocity in this region, the frequency can be read as twice in Figure 6, but increased to four times in Figure 9. In this data characteristic, for example, one can estimate that some difficulty occurs with the rotation of the ball 30, in which, for example, the ball 30 is moved by wear of the ball seats A1 and A2 to a secondary side of the ball seat A2 to increase a pressing force and increasing a dynamic friction force. Thus, this can be used for, by way of example, prediction of a failure with frictional wear of the ball seats A1 and / or A2 or deterioration of the sealing surface.
    [0306] Furthermore, a change in time until reaching the region T 1 , that is, time required from the moment when an air pressure is supplied to the actuator 2 to the ball 30 begins rotation, can also be used for failure prediction. Specifically, in Figure 6, region T 1 starts from a time of about 1000 milliseconds, and a time lag from supplying air pressure to actuator 2 to rotation is on the order of one second. On the other hand, in Figure 8, it starts from a time around 350 milliseconds. Thus, as the valve open / close count increases, this time delay decreases. From these data characteristics, it can be estimated that the static friction force of the ball seats A decreases.
    [0308] Furthermore, the duration of the T 1 region can also be used for failure prediction. Specifically, while the T 1 region can be read as approximately 1000 milliseconds to 1800 milliseconds in Figure 7, it is approximately 350 milliseconds to 1500 milliseconds in Figure 8. As the valve open / close count increases, the time required for the region T 1 , that is, the time required for the rotation of the ball 30, increases. From this data characteristic, it can be estimated that an increase in the dynamic friction force of the ball seats A occurs. Thus, this can be used for, by way of example, prediction of failure with frictional wear of the bearings. ball seats A.
    [0310] From Figure 5 to Figure 9, the T 2 region is a small band with a degree of opening close to about 30 degrees, and this corresponds to, as the ball 30 operates, a state in which the ball rotates further. (degree of opening from about 20 degrees to 30 degrees) near about from the state in Figure 12. Near this region T 2 , a state is included in which, from an entire peripheral surface contact state in the region T 1 , the through path 30a of the ball 30 reaches the ball seats A to transition to a partial contact state and, with the valve opening, the fluid pressurizes the inner wall of the through path 30a of the ball 30 to cause a force in a valve opening direction to act on ball 30. In the present example, fluid flows from left to right in Figure 10 to Figure 14.
    [0312] This action of the valve opening force by the fluid is also trapped in the angular velocity graph (characteristic graph) as a significant increase. Specifically, while the local maximum value near the T 2 region in Figure 6 can be read as approximately 44 degrees / second, the local maximum value in Figure 8 near it is approximately 63 degrees / second. Thus, an increase in the local maximum value of the angular velocity can be read with the increase in the count of valve openings / closings. Based on this data characteristic, a decrease in the dynamic friction force of the ball seats A can be estimated to occur. Thus, this can be used for, for example, prediction of failure with frictional wear of the ball seats A In a state in which the ball 30 makes partial contact with the ball seats A1 and A2, in addition to a decrease in the dynamic friction force, with a force applied to the rotational direction of the ball 30 by the action of the fluid pressure, the decrease in dynamic friction force proceeds further. Thus, the fluid pressure is captured as a friction element is suitable in the T 2 region.
    [0314] Also, as with the T 1 region, a time to reach the T 2 region can also be used for failure prediction. While the T 2 region occurs at about 2300 milliseconds in Figure 6, it occurs at about 2000 milliseconds in Figure 8. Thus, the time decreases as the valve open / close count increases, and the rotation begins at one point. early phase. Thus, it can be estimated that the static friction force or dynamic friction force of the ball seats A decreases, and this can be used for prediction of failure with frictional wear of the ball seats A.
    [0316] From Figure 5 to Figure 9, region T 3 is a region from a degree of opening of about 80 degrees to a fully open state (a degree of opening of 90 degrees and an angular velocity of 0), and this corresponds to , as the operation of the ball 30, a state from Figure 13 to Figure 14. In this region T 3 , a state is included in which a transition is made from the partial contact state to the entire peripheral surface contact state again with respect to the ball seats A and a transition is made from the dynamic friction force to the static friction force.
    [0318] In region T 3 , while a trend is indicated in Figure 6 in which the magnitude of the angular velocity decreases from approximately 42 degrees / second, a decreasing trend from approximately 30 degrees / second is indicated in Figure 8. According to This data characteristic, even if a transition is made to the state in which the ball 30 seals with the entire peripheral surface of the ball seats A1 and A2, this does not lead to a decrease in angular velocity. Thus, it can be estimated that, for example, a decrease in the dynamic friction force occurs, and this can be used for prediction of failure with frictional wear of the ball seats A.
    [0319] The duration of the T 3 region can also be used for failure prediction. Specifically, while the T 3 region can be read as roughly 3500 milliseconds to 4000 milliseconds in Figure 7, is approximately 3500 milliseconds to 4100 milliseconds in Figure 8. As the valve open / close count increases, the time required for the T 3 region, that is, the time required for the valve opening / closing count increases. ball rotation 30, increases. From this data characteristic, it can be estimated that an increase in the dynamic friction force of the ball seats A occurs. Thus, this can be used for, by way of example, prediction of failure with frictional wear of the bearings. ball seats A. Note that although the state is exemplarily depicted in the present example in which the time increase required as valve 3 open / close count increases in region T 3 , this does not mean that it is restrictive and the wear state of the ball seats A1 and A2 can be sensed with reference to a state in which the required time decreases.
    [0321] Next, a description is made of the results of measuring an actual wear amount of the ball seat A2 in the examples of the test number 10 described above. Note that Figure 24 is a schematic descriptive diagram describing this measurement situation. In the measurement, after operation at each open / close count (thirty times, five hundred times, one thousand times, and ten thousand times), the ball valve 3 was disassembled to remove the ball 30 and the secondary ball seat A2 and As depicted in the schematic diagram of Figure 24, the removed ball seat A2 was placed on an appropriate horizontal surface and, with the removed ball 30 placed on its sealing surface, a total height h was measured from one side of bottom surface of ball seat A2 to apex of ball 30 for each count of openings / closings. That is, according to an increase in the amount of wear of the ball seat A2, this total height h decreases slightly and, therefore, from that amount of decrease, at least the degree of a state of wear can be grasped (the height total h is referred to as "dimension G" of ball seat A).
    [0323] Actually, the amount of decrease = 0.26 mm was the same between the open / close count of thirty times (corresponding to Figure 6) and the open / close count of five hundred times (corresponding to Figure 7). However, the amount of decrease = 0.36 for the count of openings / closings of one thousand times (corresponding to Figure 8) and the amount of decrease = 0.48 mm for the count of openings / closings of ten thousand times (corresponding to Figure 9), and thus it was confirmed that the amount of decrease increases as the drive count increases and the wear actually proceeds. Note that as a result of checking the actual sealing surface by visual inspection after actuation with each count of openings / closures, a change of the sealing surface was hardly observed in the counts of openings / closings of time zero and thirty times but a linear or groove-shaped trace of contact with the ball was observed in the count of thousand times open / close and a sign of friction with a metal (ball) and a band-shaped contact trace was observed in the ten thousand times open / close count.
    [0325] Note that valve seal leakage was confirmed after actuation ten thousand times in the present example. Therefore, with acquisition of at least the angular velocity data in Figure 9, prediction of failure due to ball seat wear etc. can be performed. and life expectancy.
    [0327] A general outline of the condition monitoring process is described below in Figure 15 through Figure 17 (test number 2) and Figure 18 through Figure 20 (test number 8). Also in each of Figure 15 to Figure 20, regions T to T 3 indicate the same similar meaning as above. From these graphs, as with the previous ones, valve status monitoring can be done.
    [0329] That is, when reading the time until reaching the region T 1 , the duration, or a change in frequency of appearance of the peak of local maximum or local minimum of the angular velocity in that region according to the count of valve openings / closings, at least the state of wear of the ball seats can be inferred and used for valve failure prediction. Also in the T 2 region, by reading a change in the position or magnitude of the local maximum peak according to the count of openings / closings, at least the wear state of the ball seats can be inferred and used for prediction of failure of the ball seats. valve. However, in Figure 16 and Figure 17 (test number 2), the position of the local maximum peak differs from the other results, and can be found to shift to a position near a T 2 'region (a small band with an opening degree close to about 40 degrees). Also in the region T 3 , when reading a change in time and duration until reaching that region or in the rate of change of the angular velocity in that region according to the count of openings / closings, at least the state of wear of the seats of ball can be inferred and used for valve failure prediction.
    [0331] Below, in each of Figure 21 to Figure 23 (test number 11), although no structural diagram is depicted, but an example of a graph of angular velocity acquired from the gyro sensor is depicted using the gyro sensor monitoring unit. the present invention when the valve body rotates from fully closed to fully open 90 degrees in a double acting pneumatic actuator in a rack and pinion structure and a butterfly valve type quarter turn. Chart mark details are similar to above, and the test conditions correspond to test number 11 in Table 1.
    [0332] Specifically, this butterfly valve has a center-type butterfly valve structure made by casting in an aluminum die and having a nominal pressure of 10 K and a nominal diameter of 50 A. At its valve stem, the pressure monitoring unit the present invention is connected in a manner similar to the way described above. The graphs in the drawings are also similar to the above, and angles by encoder measurement and angular velocities acquired by the gyro sensor (Y-axis measurement values) incorporated in the monitoring unit are put in graph form. The diagnostic target is a rubber seat made of EPDM. Also, Figure 21 represents data acquired after opening / closing with the count of open / closes of zero time, Figure 22 after five hundred times, and Figure 23 after fifteen hundred times.
    [0334] Also in Figure 21 to Figure 23, each of the T 1 and T 2 regions means the same as above. From these graphs, valve status monitoring can be done in a similar way to the previous one. That is, the region T 1 is a region where the valve body leaves the state of making contact with the rubber seat, and it is also a region where a phenomenon called jump occurs. In this region, as the actuation is repeated with the count of openings / closings five hundred times and then fifteen hundred times, a change in the increasing / decreasing trend of the angular velocity can be observed. Based on this data characteristic, for example, this can be used for failure prediction with frictional wear of the rubber seat and deterioration of the sealing surface.
    [0336] Also in region T 2 , the valve body leaves the rubber seat to be oriented with an intermediate degree of opening. In this state, fluid unbalanced torque acts on the valve body, causing the valve body a to open even more easily. As the actuation is repeated with the count of openings / closings to five hundred times and then fifteen hundred times, an increase in angular velocity can also be read becomes pronounced, and a trend in which the time shortens until reaching the region T 2 . Based on this data characteristic, this can be used for prediction of failure with frictional wear of the rubber seat, for example, in a vertical direction (around the stem) of the valve body.
    [0338] Next, Figure 25 to Figure 30 each represent a graph of angular velocity acquired in another example different from the example described above. In this other example, tests were substantially performed on the same conditions as test number 10 described above (conditions including horizontal plumbing using the ball valve depicted in Figure 1, water vapor, and 1.0 MPa), and graph mark (such as the amount indicated by each shaft and linetypes) is also similar to Figure 5 etc. However, unlike the example described above, angular velocity data is also measured on the X axis and Z axis (other than the roll axis) of the gyro sensor 7 represented in Figure 1. That is, Figure 25 is a graph in which angular velocity data in the X-axis direction at initial motion is put into graph form, Figure 26 is a graph in which angular velocity data in the Y-axis direction at initial motion is plotted graph form, and Figure 27 is a graph in which angular velocity data in the Z-axis direction in initial motion is plotted. Thus, Figure 5 and Figure 26 represent graphs of angular velocity under substantially the same conditions.
    [0340] Also, from Figure 28 to Figure 30 are graphs of angular velocity after the valve opens and closes twenty thousand times after initial movement from Figure 25 to Figure 27, angular velocity data in the X-axis direction in Figure 28, in the Y-axis direction in Figure 29, and in the X-axis direction in Figure 30 are put into graph format, in a manner similar to those of Figure 25 to Figure 27. Thus , Figure 28 corresponds to Figure 25, Figure 29 corresponds to Figure 26, and Figure 30 corresponds to Figure 27. In particular, it can be said that Figure 29 represents data acquired after Figure 9, which is a graph after the valve opens and closes ten thousand times under substantially the same conditions.
    [0341] As shown in Figure 26 and Figure 29, from the graphs of angular velocity in the Y-axis direction, a trend similar to that of the other graphs in the Y-axis direction can be read. In particular, in Figure 26, as with Figure 5, one or a plurality of peak-like features appear in the T 1 region, at least one pronounced pattern appears near the T 2 region, and a decreasing pattern appears in the T 3 region. Also in Figure 29, features substantially similar to the previous ones are acquired. However, compared particularly with Figure 9, although the peak-like feature (maximum value) in the T 2 region is more significant, a gradual pattern is acquired in which the angular velocity decreases as a whole. In any case, it can be said that traits are acquired that are easy to catch.
    [0343] On the other hand, in Figure 25, Figure 27, Figure 28 and Figure 30, which are graphs in relation to directions other than the Y-axis directions, at least no significant features appear as described above, and they observe many random amplitudes that are not easy to grasp. Thus, as the angular velocity data to be put in the form of a graph, it can be said that the angular velocity data in the rotation direction of the tipping axis (Y axis) is preferable.
    [0345] Next, in Figure 31 and Figure 32, the valve status sensing system of the present invention is described. The present invention is directed to a valve status capture system, and the system includes valve 3, a sensor unit 1 attached to this valve 3, and a server 41 communicatively connected to this sensor unit 1, on the basis From a trait value included in measurement data measured by sensor 7 included in sensor unit 1 of a valve stem 4 that opens and closes valve 3, a wear state of a wear component (A, B, C).
    [0347] In Figure 31, valve 3 is the above-described ball valve depicted in Figure 1, and sensor unit 1 is also the previously described monitoring unit 1 depicted in Figure 1. Also, as depicted in Figure 2, as with monitoring unit 1, sensor unit 1 is attached pluggable and detachable as a single independent unit including a power supply 11 in a mode capable of simultaneously rotating with valve stem 4, and is connected via communication module 10 via internet 43 to server 41 etc. when using a default wireless communication protocol to allow wireless communication. Also, as the wear component, the ball seats A described above are selected.
    [0349] In Figure 31, a tablet 44 and a PC 45 are examples of a terminal for checking information regarding valve 3 to be transmitted from the sensor unit 1, and include display means capable of displaying transmission data from the sensor unit. sensor 1. For these display means, for example, any display application can be used that can be purchased from an application server included in the server 41.
    [0351] In Figure 31, server 41 uses a cloud server. The cloud server is suitable for various computing processes and security measures described further below. Also, the server includes a database and all or part of failure diagnosis means not shown, which will be described later. Furthermore, the server can include a default application server for terminal exposure or something similar. In this case, a user who has a terminal can access the server anytime and anywhere to view a valve status.
    [0352] A measurement data trait value for use in capturing valve status can be a time from fully open of valve 3 to a predetermined degree of opening that appears on an angular velocity graph (Figure 5 to Figure 9, Figure 15 a Figure 23, Figure 26 and Figure 29) acquired from angular velocity data in the central axial direction (Y-axis direction) of valve stem 4 (for example, a tempo T from 0 degrees until the opening degree reaches 10 degrees and a time T 2 from 0 degrees to 30 degrees), a time from fully closed to fully open to fully closed, or a time from a predetermined opening degree to fully closed (for example, a time T 3 from 80 degrees to that the opening degree reaches 90 degrees). Also, the trait value can be the number of steep gradients and the position, magnitude, and / or width of each steep angular velocity gradient included in a predetermined time region (for example, the time region T 1 or T 2 ), it can be a time until the angular velocity reaches a maximum value or a local maximum value or the magnitude or width of the maximum value or the local maximum value, or includes all or part of these. Furthermore, the trait value can be a start / end time of a predetermined time (such as time T 1 ) and, as for a leak value, it can be a value indicating the presence or absence of a leak (value binary). Based on these types of trait values, trait data is generated as numeric data (scalars, vectors).
    [0354] Here, for example, as appears in each of Figure 5 through Figure 9, Figure 15 through Figure 20, Figure 21 through Figure 23, and Figure 25 through Figure 30, the steep gradient indicates a portion of one or some of a plurality of points at uneven positions twisted with respect to the time axis between fully open and fully closed on an angular velocity graph in which the valve opening degree changes abruptly. A gradient to be read as a steep gradient (rate of change) can be set as appropriate according to the implementation. For example, any of the following gradients can be read as a steep gradient: a gradient from a unimodal locus depicted in the T 1 region of Figure 5 to Figure 9, from Figure 15 to Figure 20, and from Figure 21 to Figure 23; a gradient near region T 2 from Figure 5 to Figure 9, Figure 19, Figure 20, and Figure 23; and a gradient near the T 2 'region in Figure 16 and Figure 17.
    [0356] Also, the number of steep gradients is, for example, the number of steep gradients that appear on a graph and their readable times. The position of a steep gradient can be a time when it starts or ends that steep gradient or a time in the middle of these times or, in the case of a unimodal place, a time at a local maximum value. Also, a steep gradient shift is a difference between values (degrees of opening or angular velocities) corresponding to the start and end times of that steep gradient and, in the case of a unimodal location, it can be set to the peak height of an appropriate local maximum value. Similarly, the width of a steep gradient is, for example, a difference between the start and end times of that steep gradient and, in the case of a unimodal location, it can be set to a width according to the peak height of a value. appropriate local maximum.
    [0358] In this way, if an easily grasped feature appears in the data pattern that can be acquired according to valve opening and closing, a time can be reduced or optimized, the size of the amount of information required to process in the statistical operation of data described further. later. In particular, since the angular velocity graph by the gyro sensor can be easily characterized, teaching data (test data) is easily generated, as further described below. In a sensor other than the gyro sensor, a feature is difficult to appear in the data pattern that can be acquired according to valve opening and closing. Thus, when this information with fewer features is used for machine learning, separate statistical processing is required to extract features and use most or all chunks of the acquired data. However, in the angular velocity graph data for use in the present invention, a steep characteristic gradient readily appears. Thus, only with this less information in relation to steep gradients (a set of several numerical values such as position, number, offset and / or width), can statistical operation be performed with high precision, thereby leading to savings of computing resources.
    [0360] By using these pieces of trait data acquired from the angular velocity graphs, the first fault diagnosis means, the second fault diagnosis means, or the third fault diagnosis means perform valve status acquisition in the present invention of as follows. The means that perform each function described below are not particularly restrictive, and can be provided to the system as appropriate according to the implementation.
    [0362] In the first anomaly diagnosis means, a database 42 has stored therein a first reference data table (not shown) formed of a plurality of pieces of tag data and feature data according to a predetermined count of valve openings / closings for each specific condition, sensor unit 1 and / or server 41 are provided with first fault diagnosis means configured to capture a state of wear and perform a valve fault diagnosis 3, these first anomaly diagnosis means include specific data generation means that generates specific data formed of a specific condition of valve 3, a count of openings / closings of valve 3, and specific trait data based on data from angular velocity, data acquisition means acquiring from a first reference data table first reference data having an open / close count equal to the open / close count of the specific data and a closest specific feature value, and comparing and determining means comparing any chunk of this acquired tag data contained in the first data of reference and a predetermined threshold to acquire a predetermined determination result.
    [0364] A label is, for example, dimensional data or leak quantity data, and label data is a numeral value of the label. In the present example, dimensional data or leak amount data is used as label data. For the label, it is suitable to use a characteristic value of a type that is important for state acquisition of the state of wear of a wear component of valve 3.
    [0366] An example of the dimensional data is, for example, in the case of ball seats A, the dimension G depicted in Figure 24 described above, and is formed from dimensional data of any part of a wear component in a wear-free state. and decreases according to the increase in the amount of wear. The leakage quantity data is, for example, in the case of valve 3, in the fully closed state shown in Figure 14, a value measured by a predetermined measuring device the quantity of the fluid leaking between the ball 30 and the ball seats A, and is a characteristic value in which the sealing performance of the valve is directly reflected. As the amount of leakage is more, the valve condition is evaluated as being more degraded.
    [0368] The first reference data is, for example, a record in each row indicated in the following Table 2 (an example of a reference data table), and is formed of, for each specific condition and according to the count of openings / closings valve 3 that includes a specific wear component, a plurality of tag combinations (valve open / close count, amount of wear per dimensional friction of the ball seats, and the presence or absence of leakage) and a combination of trait data (start time of the T 1 region and local maximum value near the T 2 region). Specific conditions are various conditions required to identify a valve in a state of use, such as the valve type and product manufacturer name, as well as conditions of use (such as the installation environment including temperature and fluid in use. ) and the type of the wear component and the dimensional data part. The first reference data acquires, under the same specific conditions, from the valve as a measurement target, data according to the first reference data that includes angular velocity data, and is accumulated in advance in the database 42. The first data Accumulated reference numbers are managed as classified by the specific condition, and a sufficient amount of data is acquired in advance according to the plurality of tag combinations.
    [0370] Also, the angular velocity data for use in at least the first anomaly diagnosis means includes data required to acquire an angular velocity graph and to be measured by the gyro sensor 7, as well as information regarding the count of openings / closings of valve 3 and the specific condition. Furthermore, as for the open / close count of valve 3, for example, if the number of measurement times is defined in advance for each specific condition, records of the open / close count can be made uniform. Thus, when the data acquisition means described further below refer to the first reference data table, the open / close count of the specific data and the open / close count of the record of a referent can be matched. .
    [0372] Therefore, as for the first reference data, only with the sensor unit 1 connected to the valve to start, the first reference data under various specific conditions can be easily acquired by, for example, a manufacturing or maintenance firm. of valves, and accumulate in the database without disturbing the actual operation of the valve. Also, the trait-specific data means a piece of trait data selected in advance from the trait data, and a remarkable feature value with a strong correlation trend with the label is selected.
    [0374] [Table 2]
    [0375]
    [0378] The specific data generation means are means that identify and read, of graph data acquired by conversion from angular velocity data (raw data) measured by the gyro sensor 7 to graph data of angular velocity in the Y-axis direction. , a specific trait value that appears on this graph, and they combine a specific condition of this valve 3 and the valve open / close count at the time of this measurement and output them as a set of numerical values. Note that the graph data acquired in this memory can be output to a predetermined display device in order to display.
    [0380] The data acquisition means are means that take specific data as input; they access the reference data table of the database 42 to find a table that matches a specific condition included in this specific data; if the table matches, they refer, from this table, to a record with the count of openings / closings equal to the count of valve openings / closings included in the specific data and acquires a specific trait value (registration trait value) of a record corresponding to a specific trait value (specific data trait value) included in the specific data; and, furthermore, it determines whether this record trait value is substantially equal to the specific data trait value. Here, as appropriate, a range is set in advance in which they are determined to be substantially equal to each other.
    [0382] The means of comparing and determining is means that take, as inferred tag data from valve 3, a plurality of pieces of tag data included in a record having a record feature value determined as being substantially equal to the value of specific data feature, compares this inferred label data with a plurality of thresholds each set in advance for each of the label data and, according to the comparison result, outputs a predetermined determination result. For example, when data from Inferred label are equal to or greater than the threshold, as the determination result, default warning information (alert) is output. When the label data is less than the threshold, predetermined information regarding the current state is output as a result of determination. For example, when the safest measure is taken, if any piece of tag data exceeds the threshold, an alert is raised.
    [0384] Here, a specific way of reading Table 2 is described. In a series of drawings indicated in the table, in a region where the valve opening degree is completely close to an opening degree of about 10 degrees (region T 1 ), for example, when the valve open / close count is a thousand times (Figure 8), the timing when the angular velocity starts to increase is earlier compared to the case of five hundred times (Figure 7), that is , 350 milliseconds, which is significantly below 1000 milliseconds from the start of the valve open operation. Here, the total height decrease amount (h dimension in Figure 24) of the ball seat is 0.36mm, which is five hundred times larger than the case (0.26mm decrease amount), and it can be grasped The ball seat is beginning to wear out.
    [0386] These pieces of information are stored in advance by the valve manufacturer, the maintenance firm, or the like in memory 9, server 41, or the like as reference data, and then compared to actual measurement data (measurement data). angular velocity) of valve 3 for use in an operating plant or something similar, thereby allowing the state of wear of the ball seat in which valve to be captured.
    [0388] Specifically, in the actual measurement data of the valve with the open / close count of a thousand times, if the timing of an increase in angular velocity in the T 1 region is 400 milliseconds, this value is close to the data of 350 millisecond reference, and thus a situation can be inferred where the ball seat as the sealing member has worn almost 0.36mm. Note that the timing of an increase in angular velocity in region T 1 is determined only from one point, 400 milliseconds, this can be determined based on a plurality of values such as an average value per unit time. Here, while the time required to open and close the valve in the present example can be captured using a built-in clock in CPU 8, another separate timer can be used. Also, the valve open / close count is counted using, in addition to the encoder, a microswitch (travel limit) that detects a fully open / fully closed valve position, or something similar.
    [0390] In a small region where the valve opening degree is about 30 degrees (region T 2 ), for example, when the valve open / close count is a thousand times (Figure 8), the value of a velocity The sharply increasing angle is larger compared to the case of five hundred times (Figure 7), that is, 63 opening degrees / second (rad / s), which is significantly over 45 opening degrees / second. Here, as described above, the amount of decrease in the total height (h dimension in Figure 24) of the ball seat is 0.36 mm, which is greater than the case five hundred times (amount of decrease in 0.26 mm ), and it can be seen, from the sudden increase in angular velocity in the region T 2 , that the ball seat is proceeding to wear.
    [0392] These pieces of information are stored in advance by the valve manufacturer, the maintenance firm, or the like in memory 9, server 41, or the like as reference data, and then compared to actual measurement data (measurement data). angular velocity) of valve 3 for use in an operating plant or something similar, thereby allowing the state of wear of the ball seat in which valve to be captured.
    [0394] Specifically, in the actual measurement data of the valve with the open / close count of a thousand times, if the angular velocity in the T 2 region is 65 (rad / s), this value is close to the reference data of 63 (rad / s), and thus a situation can be inferred where the ball seat as the sealing member has worn almost 0.36mm.
    [0396] Furthermore, as for a specific way of reading Table 2, in combination with valve leakage data, the life of the sealing component can be predicted based on the measured angular velocity. Specifically, when the valve open / close count is ten thousand times (Figure 9), the amount of decrease in the total height (h dimension in Figure 24) of the ball seat is 0.48 mm, which is larger than the case of a thousand times (0.36mm decrease amount), and it can be seen that the ball seat is proceeding to wear. And, since a valve seat leak is confirmed in the valve, it is determined that the life of the ball seat ends when the valve open / close count reaches ten thousand times. Here, the valve seat leakage test for the valve in the present example was performed under the condition of using nitrogen as the test fluid and this fluid pressure is 0.6 MPa.
    [0397] These pieces of information are stored in advance by the valve manufacturer, the maintenance firm, or the like in memory 9, server 41, or the like as reference data, and then compared to actual measurement data (measurement data). angular velocity) of valve 3 for use in an operating plant or the like, thereby allowing the life of the ball seat in which valve to be predicted.
    [0399] Specifically, for example, in the actual measurement data of the valve with the open / close count of a thousand times, if the timing of an increase in angular velocity in the T 1 region is 400 milliseconds or the angular velocity in the T 2 region is 65 (rad / s), this can be determined to be the state of the valve from the reference data in Table 2, and the ball seat life ends with the count of openings / closes ten thousand times, and maintenance can be performed on a scheduled basis before the valve open / close count reaches ten thousand times.
    [0401] Still further, as for a specific way of reading Table 2, in combination with the dimension or consumption data that serves as a reference for replacement of the sealing component, the life of the sealing component can be predicted based on the angular velocity. measure. Specifically, if the reference for substitution is such that the amount of decrease in the total height (dimension h in Figure 24) of the ball seat becomes 0.40 mm, it is determined on the basis of a proportional relationship between the count of 1000 times valve open / close and the ten thousand times in the reference data in Table 2 that the ball seat life ends when the valve open / close count reaches three thousand times.
    [0403] Specifically, in the actual measurement data of the valve with the open / close count of a thousand times, if the angular velocity in the T 2 region is 65 (rad / s), this value is close to the reference data of 63 (rad / s), and thus a situation can be inferred where the ball seat as the sealing member has worn to almost 0.36mm and the life can be determined to end with the above-described count of three thousand times.
    [0405] Note that as for data for use in the first anomaly diagnosis means, for example, as depicted in Table 2, trait data with two (or more) pieces of tag data is accumulated in the database as data. test, and thus this is a problem called multi-labeling (multi-class classification).
    [0406] Thus, a known learning model in relation to multiclass classification can be applied to the accumulated baseline data.
    [0408] Next, the second and third fault diagnosis means perform fault diagnosis by means of a machine learning scheme with a single label. In database 42, a predetermined learning model generated on the labeling training database is stored. Inferred tag data for use in these second failure diagnosis means is an inferred value derived from the learning model.
    [0410] The learning model described above is generated as follows, for example. In the state of the same specific condition, in an interval in which label data (dimension, amount of leakage) can be considered the same, the valve opens and closes a sufficient number of times to acquire angular velocity data, and, from these, each piece of trait data is generated (that is, a trait value is read from a graph of angular velocity). For these, the same tag data is provided to generate teaching data for training. These teaching data chunks are sampled in sufficient quantity for each label data chunk and stored in database 42.
    [0412] For a group of samples of the teaching data for each piece of the same label data, machine learning (statistical operation) is applied to generate a model (identification model or generation model). While this can be taken as a learning model, it can also be examined by test data, an optimal statistical model can be found, or a group of parameters can be adjusted for each statistical model, thereby improving precision and reliability. . Therefore, with a so-called supervised machine learning scheme, a learning model is generated. Like machine learning, selection and improvement can be made as appropriate according to the implementation. For example, a known scheme can be applied as appropriate. If the label data have continuous values, a regression scheme is usually taken (such as linear regression, logistic regression, or SVM). In this case, the learning model corresponds to a regression function f that can be inferred as "inferred label data = f (trait data)", and the function is identified with a default parameter.
    [0414] Furthermore, it can be considered the case that one wear component is replaced by another component in the course of valve operation and the tag data for that other replaced component has not been sufficiently sampled by advance or are not present at all. In this case, there is no learning model of the replacement component present in the database, and thus the failure diagnosis means cannot be executed. In this case, the learning model stored in the database can be corrected for use. For example, a scheme known as transfer learning can be taken. For example, the tag data from a known learning model can be given a predetermined weight to correct and use the tag data for the replacement component.
    [0415] On the other hand, the sensor unit 1 and the server 41 are provided with fault diagnosis means not shown and configured to detect a state of wear and to carry out a fault diagnosis of the valve. These anomaly diagnosis means are formed of at least feature value generation means that generate predetermined feature data, inferred tag data calculation means that calculate (scalar) tag data by means of machine learning on the basis of trait data, and comparing and determining means comparing this tag data with a predetermined threshold to acquire a determination result.
    [0417] The trait value generating means identifies and reads, from graph data acquired by converting angular velocity data (raw data) measured by the gyro sensor 7 to angular velocity graph data in the Y-axis direction, each trait value that appears on this graph, and is output as trait data formed from a plurality of sets of numerical values. Note that the graph data acquired in this memory can be output to a predetermined display device in order to display.
    [0419] The inferred tag data computing means is means that takes trait data as input and applies this trait data to a learning model called from database 42, thereby calculating and outputting tag data as inferred value. In case of a plurality of labels (dimensional value, leakage value), each learning model is called according to the type of label.
    [0421] The comparing and determining means takes the inferred label data as input, compares this label data with a threshold set and stored in advance according to the label, and outputs predetermined warning (alert) information as a result of determination when the data Inferred label data exceeds the threshold and outputs predetermined information regarding the current state as a result of determining when the inferred label data is less than the threshold. When the determination results for a plurality of labels are mutually contradictory, the determination result is associated with any one of these as appropriate. Note that instead of this binary return (OK, NG), a plurality of thresholds can be set and a determination result corresponding to the interval of each threshold can be set.
    [0423] For example, as for dimensional data, a first threshold can be set to an amount of wear evaluated as failure (replacement required); wear quantity smaller than this first wear quantity, for example, data of a wear quantity corresponding to a period of three months before evaluation is made as failure (wear quantity three months before) when using a valve of the same type in normal use condition can be purchased separately in advance; and this amount of wear can be set as the second threshold. For example, when the inferred tag data value is equal to or greater than the second threshold and is less than the first threshold, a message indicating three months before replacement is required as a result of determination. Similarly, as for wear thresholds (which have a smaller value as the predetermined period is longer), which are acquired in time series according to the amount of wear before the predetermined period (the amount of wear before the predetermined period), In the order of value, a plurality of wear thresholds can be set to make the determination results extremely more accurate. Outputs of these multiphase determination results can be performed similarly for leak amount data.
    [0425] Note that as for the diagnostic timing carried out by the first and second fault diagnosis means described above, for example, a diagnosis can be carried out by an instruction from a user by means of a terminal or it can be carried out each time it is opened. and closes the valve. Alternatively, the timing can be set with a predetermined valve open / close count or at predetermined time intervals.
    [0427] Additionally, means can be provided that transmits the determination result to an application in the terminal so that it can be displayed and means that notify a management server managed by the valve manufacturer (in charge of maintenance) of the determination result. .
    [0429] The teaching data (test data) using the label described above is prepared in advance in the database 42 as a learning model for each label (characteristic value) of a wear component in the condition specific to a valve such as a valve or a fluid to use. Thus, only by applying the trait data to this learning model can a diagnosis be made. Thus, while it is required to collect teaching data (test data) and generate learning models in advance, high-speed diagnostic processing can be performed during the actual operation of valve 3, and resources for configuration can also be reduced. system.
    [0431] Furthermore, unlike the scheme of the abnormality diagnosis means described above, the valve status sensing system of the present invention can also be configured by an unsupervised machine learning scheme. Also in this case, the database 42 can be used as a data store in the same way as the trait data described above. The anomaly diagnosis means by this scheme are the third anomaly diagnosis means, and include at least data accumulation means, data control means, model data computing means, index calculation means, and means of comparison and determination.
    [0433] The data accumulation means generates the same trait data as described above from the angular velocity graph data acquired from the angular velocity data measured by the gyro sensor 7, and transmits this trait data to the database. data 42 and causes the trait data to be stored in the database 42 in a predetermined format to generate accumulated trait data. The data accumulation means may use, as appropriate, the means for conversion from angular velocity data to graph data and the trait value generating means described above. This data storage is controlled by the data control means. The data control means controls the data accumulation means so that the acquired trait data is stored in the database 42 each time the valve is opened and closed until the trait data of a predetermined amount set by advance is accumulated in the database 42. When the accumulated data reaches the predetermined amount, this is detected, and a notification as such is made to the model data computing means.
    [0435] The model data computing means reported as such applies machine learning to all chunks of trait data accumulated in database 42 at this time (accumulated trait data) to generate a learning model. An output value from this learning model is referred to as consumption data. Therefore, the learning model is generated by a schema of a called unsupervised machine learning. This consumption data is called normal data, and is required to be data acquired and accumulated while the valve is operating normally.
    [0437] Thus, as machine learning in this case, selection and improvement can be made as appropriate according to the implementation. As a known scheme, for example, a dimensionality reduction scheme (such as PCA or SVD) is taken. For example, in the subspace method, a subspace U in normal operation is generated taking, as a basis, vectors higher k in a single group of vectors (principal component with subscript in the distribution) acquired by performing principal component analysis using all the cumulative trait data chunks (taken as an N-dimensional vector) at the time of normal operation. This computation is performed by the model computational means. Thus, the learning model supports an nxk (second-order tensor) matrix.
    [0439] The index calculating means calculates and outputs a predetermined index defined between feature data (new feature data) by data of acquired initial valve opening / closing angular velocity after the data control means notify the operators. model computing means and consumption data described above.
    [0441] In the subspace method described above, a degree of anomaly (index) can be defined as the predetermined distance between the normal subspace generated by the model data computing means and the new feature data (unknown data). For example, when a subspace U acquired from the group of normal data is ( m , ... u k ) and unknown data are x = (x 1 , ... xn ), a degree of anomaly can be defined d 2 = x T xx T U k U Tk x.
    [0443] The means of comparison and determination compares the index described above with a threshold set and stored in advance and, for example, outputs, as abnormal outliers, predetermined warning (alert) information as a result of determination when the index becomes equal or greater than the threshold and output predetermined information regarding the current state as a result of determining when the index is less than the threshold.
    [0444] Next, Figure 32 depicts a general sketch of a valve status pickup process in accordance with the present invention. First, sensor unit 1 is connected to valve 3 as a target. Specifically, the unit is fixed in the above-described mode depicted in Figure 1. Typically, the sensor unit 1 is a single independent unit automatically continued to monitor valve 3 once after it is connected, and thus its power supply must be checked, such as sufficient load power. Also, normally, the unit is made to perform wireless communication as shown in Figure 31, and thus it is also required to check a communication status with necessary communication targets, such as cloud server 41, terminals 44 and 45 via the internet 43.
    [0446] In Figure 32, at initial setting 46, the open / close position of the valve is precisely set for the gyro sensor 7, and information is set in relation to the valve 3 (such as the type and manufacturer of the valve. , environment of use and fluid of use) for the sensor unit 1. In particular, information is also set in relation to labels (such as dimensional values, amount of leakage, and thresholds). After completion of the initial setting 46, the valve 3 is actually operated.
    [0448] In Figure 32, processes collectively provided with a reference numeral 47 correspond to a general outline of the diagnosis process by the first-third-party above-described anomaly diagnosis means. As described above, in the first and second fault diagnosis means, it is required to store predetermined data in advance in the database 42 of the cloud server 41. Thus, to execute the first and second fault diagnosis means , tag values have to be acquired in advance, that is, a sufficient number of sample data chunks such as a specific dimensional value of a specific wear component and an amount of leakage from a specific valve in a specific condition.
    [0450] In process 47, graph data is first acquired at a predetermined timing by graph conversion means from angular velocity data measured by the gyro sensor 7 of the valve stem 4 of the valve actually operating 3. From this data of graphically, the trait value generating means acquires trait data (a numerical value formed from a specific trait value in the first anomaly diagnosis means and a set of numerical values formed from all trait values in the second diagnosis of anomaly).
    [0452] Next, in the first anomaly diagnosis means, specific reference data is referenced by the data acquisition means. The means of comparison and determination compare a specific trait value included in these reference data and a predetermined threshold, and the determination result is delivered to the user. In the second anomaly diagnosis means, a learning model is called by the tag data calculation means inferred by the database model calling means 42, and the trait data is applied to the learning model to acquire tag data. This tag data is compared by the comparison and determination means with a threshold, and its determination result is transmitted by means of result transmission to the exposure means (terminal), thereby allowing to deliver the determination result to the user. .
    [0454] Furthermore, in the process 47, the third fault diagnosis means can be executed using the scheme described above by unsupervised machine learning. In this case, while it is not required to accumulate teaching data, but it is required to implement a program according to the product, such as the data accumulation means, the data control means, the model data computing means, the means of index calculation or the learning model adapted to the product.
    [0456] Next, fourth failure diagnosis means are described. The configuration in Figure 31 and Figure 32 is as described above. In the drawings, a valve status capture system includes valve 3, a gyro sensor unit 1 attached to this valve 3 and including gyro sensor 7, and server 41 communicatively connected to this gyro sensor unit 1 and which includes the database 42, wherein, this database 42 has stored therein a second reference data table that includes output data and product data according to a count of openings / closings of valve 3, the gyro sensor unit 1 and / or server 41 is provided with fourth fault diagnosis means configured to detect a state of wear of a wear component (A, B, C) included in valve 3 and perform a fault diagnosis of the valve 3, these fourth anomaly diagnosis means include data generating means generating measurement data including output data and product data measured by the gyro sensor unit 1 in accordance with a count of openings / closings of valve 3, data acquisition means that acquires, from the second reference data table, second reference data having output data of valve 3 substantially equal to the output data of the valve 3 included in these measurement data, and failure determination means determining prediction of failure of valve 3 on the basis of frequency of use data of valve 3 included in these second acquired reference data.
    [0457] The second reference data contained in the second reference data table includes product data and output data. Table 3 is an example of this second reference data table, and one record in each row is the second reference data. Product data is data that identifies product attributes and specifications and, in this example, as in the following, is made up of manufacturer name, valve type, wear component target part, and average usage frequency of valve (frequency of use data). As for the output data, in the present example, from a new product state (opening / closing for the first time) to a failure state (varying for each product, for example, fifty thousand times), for each opening / close (count of operations), a gyro sensor output value for each open degree stage (1 g or ® degrees to 89 degrees®90 degrees) collected in advance from the test valve with the gyro sensor attached to the it is stored in the database 42 provided on a server side in the cloud 41 as a reference value. This means that, for example, if the product is manufactured by your own company, experiments are repeatedly carried out in advance, with conditions that are varied, within the company before sale to the market and the results are stored as basic reference data. . However, the output data may not be these 0 degree to 90 degree chunks of data, but only feature parts (feature values) of the angular velocity data can be partially used as described above.
    [0458] Also, in the present example, the gyro sensor 7 may output output data in the same format as that of the output data of the second reference data as included in measurement data for each operation count. The measurement data is formed from product data and output data from gyro sensor 7 for each count of openings / closings (count of operations) of valve 3, and includes at least data included in the second reference data.
    [0459] Note that the usage frequency data described above (average valve usage frequency) can be included as appropriate also in the output data, instead of the product data. For example, on the side of a gyro sensor unit 1, the count of operations can be acquired from the valve 3 in use at a predetermined timing, and frequency of use can be calculated on the basis of this count of operations and have as output as included in the output data. Also, when the monitoring unit 1 (sensor unit 1) is connected to the valve 3 in the course of use, if information about the operation count of the valve 3 has been acquired in advance at this time, this Count of operations can be input to the monitoring unit 1 (sensor unit 1) to correct the count of operations in the output data.
    [0461] [Table 3]
    [0463]
    [0466] The data generating means is means that generates, as a measurement data chunk, measurement data (full opening degree angular velocity data) approximately one rotation from fully open to fully closed measured by the gyro sensor 7 in the form of the above-described output data and product data from valve 3 input to gyro sensor unit 1 in a predetermined format (e.g. manually input data to unit 1 or read the data by a predetermined optical read sensor ), together with the count of openings / closings of valve 3 at this moment and transmit the generated measurement data to the side of a server 41.
    [0467] The data acquisition means is means that takes the measurement data described above as input and acquires, from the second reference data table, second reference data substantially equal to the output data included in this measurement data. Here, by similarity in the output data to determine whether it is substantially the same (graph shape comparison method), an appropriate known scheme such as, for example, area comparison is selected, and means to achieve this are also implemented. Here, a specific process when the second reference data to be acquired is not present in a reference or when the output data chunks are not substantially equal to each other is further described below using Figure 33 and Figure 34.
    [0469] The failure determination means are means that refer to valve usage frequency data included in the second reference data acquired by the data acquisition means and also refer to the valve open / close count 3 included in the measurement data, and calculates a valve 3 failure timing, thereby determining valve 3 failure prediction information (what's more, it outputs the information to the terminal so that it can be displayed).
    [0471] For example, in Table 3, for a certain valve, while the average usage frequency (times / month) and the open / close count to failure are acquired in advance, and the current valve open / close count is also It is acquired from the measurement data. Thus, from these, a period (month) can be easily calculated from the current time to failure. In this case, if the data indicates three months before failure, an information notification indicating three months before the time of replacement of the ball seat can be made to the PC 45 in a service center via internet 43 or to a terminal carried by a service technician. Alternatively, reference data corresponding to "three months before" is identified from the frequency of use of each of a plurality of valves that are present in the market and, when the measured angular velocity becomes approximately equal to this reference data , a notification can be made indicating three months before failure.
    [0472] As will be described further below, since all pieces of product reference data are stored from a new product state to failure, notification of a replacement timing can be momentarily made in a staggered manner, such as three months before or Two months before. If a notification is made that encourages component replacement but no maintenance is performed, that is, for example, when the count reaches fifty thousand times, a warning may be given indicating that a fault timing has come. As will be described further below, as a predictive failure control, control continues until a leak of the fluid in use that exceeds an allowable value actually occurs to cause a system failure in which the plumbing system cannot be controlled, and terminates after acquiring output data at the time of failure.
    [0474] In a plumbing system where a plurality of valves are arranged in a single plumbing, this failure prediction ball valve control is nothing but to allow rational replacement in view of maintenance of the entire system. That is, even when servicing only one valve, the operation of your plumbing system has to be stopped, causing enormous damage under present circumstances. Therefore, all replacement is done even if there is another valve arranged that is still usable. According to the present example, since a valve with less frequency of use has a longer practical life expectancy than other valves of the same type and therefore it is not required to be replaced until the next maintenance, it is possible to simultaneously achieve reduction in the cost in relation to the replacement of component of the plumbing system and shortening of the overall maintenance time of the plumbing system.
    [0476] What's more, since data is kept for the entire period from the moment when the product is new to a moment when the product fails, even if the gyro sensor is connected to a valve whose period of use lasts up to a certain point, it can be captured the state of use. Thus, predictive failure control can be developed rapidly on the market. For example, when sensor unit 1 is attached to a valve used for half a year, a reference data search is made approximately equal to the measured angular velocity data, and a period of use is found from the corresponding count of runs. and average frequency of use. If the period of use found is half a year, this count of operations is recognized as correct, and failure prediction control can be started from an average course.
    [0478] Next, with Figure 33 and Figure 34, a fault diagnosis process is described by the fourth fault diagnosis means. FIG. 33 is a data flow diagram depicting a diagnosis process by the fourth fault diagnosis means. Process 48 is a process for determining, when these anomaly diagnosis means are first executed, for measurement data generated by the data generating means, whether a match table of the Product data included in this measurement data is present in database 42. In the drawing, for each piece of product data, if a reference data table is present it is managed in advance with an existing reference mark. Thus, with this mark, it is determined whether a table (the same product data) is present for search. If this type of table is present, the process proceeds to process 49. If this type of table is not present, the process proceeds to process A in Figure 34.
    [0480] In Figure 33, the process 49 is a process in which the measurement data is input to the database 42. In the process 50, the process is such that the data acquisition means receiving the measurement data entered into database 42 finds and acquires a table record with the same open / close count as the open / close count included in this measurement data and then determines whether the output data (angular velocity graph pattern ) of this record (acquired data) is substantially equal to the output data included in the measurement data. If it is determined that they are substantially the same, the process proceeds to process 52. If it is determined that they are not substantially the same, the process proceeds to process B of Figure 34. As a method of this comparison between two pieces of output data (a schematic determining whether they are substantially the same), any of a number of known schemes (such as the concept of distance between data and similarity in establishment and shape) can be selected as appropriate.
    [0482] In Fig. 33, in the process 52, the process is such that the failure determining means performs failure period prediction based on the count of operations. Specifically, usage frequency data (count / period) and an open / close failure count (time) included in the product data of the acquired data are acquired. On the other hand, a current open / close count (time) included in the measurement data is also acquired. From these, a predicted valve 3 failure timing can be acquired measured by the measurement data as (open / close failure count-current open / close count) / frequency of use (period). This allows to specifically acquire a predicted failure timing only with simple processing without the intervention of statistical processing (machine learning) with high processing cost.
    [0484] Note that in this process, the determination result may be to acquire with reference to, for example, a table of determination results not shown.
    [0485] For example, this table of determination results can be generated in advance for each of the same product data according to the count of openings / closings; for example, records each with a notification detail (for example, normal, warning or failure), a predicted failure timing can be prepared (for example, notification three months before or notification one month before), or something similar like name column in order of magnitude with valve open / close count as primary key; and, by means of appropriate means, with reference to a determination results table record with the same open / close count as that of the open / close count included in the measurement data, each piece of data such as the detail Notification and predicted failure timing can be acquired as a result of determination. The notification detail or the like can be divided with a plurality of predetermined thresholds. In this way, the predicted failure timing can be acquired by table reference without the intervention of computational processing.
    [0487] In process 52, a predicted failure timing is acquired. In process 53, the notification detail is acquired. These can be transmitted to the terminal by means of appropriate means so that they can be displayed. In the next process 54, it is determined whether a failure timing has come. As for this failure timing, for example, it is determined whether the predicted failure timing has come by taking a predetermined threshold as the boundary. If it is determined in this process 54 that the fault timing has come, the process proceeds to process 55. If not, the process may return to process 49 to continue abnormal diagnosis.
    [0489] Process 55 is a warning process when it is determined that the failure timing has come. In the next process 56, it is determined whether a failure has occurred. If it is determined that a failure has not occurred, the process may return to process 49 to continue abnormal diagnosis. Note that these processes 52 to 56 can be basically performed by the fault determining means but, needless to say, they can be set as appropriate according to the implementation.
    [0491] On the other hand, in FIG. 33, if a reference data table that matches the product data is not present, a process of recently generating a second reference data table on the occasion of this abnormal diagnosis. This process is process A depicted in Figure 34, and this process A is made up of processes 61 and 63. As will be described further below, since if the process proceeds to process B, which is a process to change the second table of reference data, is managed by a reference data change mark, first a determination is made in process 59 as to a reference data change mark.
    [0493] That is, when the valves are the same but have a large difference in data in a 90 degree section from fully close to fully open and a trend of a plurality of valves having a substantially similar degree of difference as above continues, This is, for example, when baseline data is limited on the basis of experiments carried out in your own company and data acquisition on the basis of the number of products after sales in the market is overwhelmingly increased, it is assumed that the data is degraded by themselves. Also, it is assumed that product data capable of identifying product attributes and specifications, such as a special fluid in use and a very wide range of outside temperature and humidity, does not match the output data even if that product data exist as reference data. In addition, it can also be assumed that there is no product data of ball valves made by another company in the first place, in other words, no reference data is stored at all. To resolve a variable degradation factor in the prediction in view of the failure prediction control, in the present example, there are two reference data generation processes A and B. Process A is referred to as the mode of newly generating data reference, and process B is referred to as a way to change reference data. Also, the entire process depicted in Figure 34 is referred to as the reference data generation process.
    [0495] In Figure 34, process 60 is a process for storing recently second reference data generated from the measurement data in database 42. For example, a case is described where a test is performed on a product manufactured by your own company before product shipment. First, as measurement data, product data is manually or automatically input from a known optical reading sensor, and then, as output data, by rotational control on the ball valve by actuator 2 connected to valve 3, the approximate assumed average valve usage frequency and angular velocity data are entered for each angle each time from fully near to fully open from a time when the product is new to a time when the product has failed by testing. This series of tests is performed N times, and data is captured as highly accurate measurement data. In the next process 61, a second reference data table is completed. In the next process 63, an existing reference data flag is set indicating which reference data is recently present and the process ends, returning to the determination detail flow.
    [0497] Next, in the process for recently generating second reference data, for example, a case is described where, for example, a ball valve of a product manufactured by another company is measured. This corresponds to the record at the bottom of the second reference data table represented in Table 3. Accordingly, in the phase where the sensor unit 1 is connected and the product data is read, it is recognized that the The product is not manufactured by the company itself, but by another company. Thus, in process A, the series of measurements are not performed N times as described above, and reference data is generated with one measurement (process 66), and the process returns to the flow depicted in Figure 33.
    [0499] On the other hand, when the product has the same product data and thus the second existing reference data table is present but this reference data table does not have reference data that is approximately the same (process 51), this requires rewriting of the second reference data itself, and a reference data change flag is set (process 59), and process B is performed. In this case, since the existing reference data is present, a change process is taken gradual.
    [0501] In process B, when output data is acquired from the measurement data (process 64), a difference is found between this output data and the existing second reference data, and the existing second reference data is increased or decreased by one. 10% of this difference and is set as new second baseline data. In processes 64 to 67, a counter C is set to 1, and angular velocity data is input as output data and undergoes similar processing repeatedly ten times, and then the process exits the loop in process 65 and marks The existing baseline is set in process 68, and then the process ends.
    [0503] With this, leveling is performed with the measurement data at least ten times. Thus, the second reference data is not rewritten with unique measurement data for only one ball valve. In particular, it is less likely that an abrupt change in the specifications of a ball seat from a ball valve manufactured by another company is entered as product data. Thus, it is quite efficient, in view of accuracy, to compare and check not only product data but also measurement data, in particular angular velocity data.
    [0505] What's more, in relation to reference data rewriting, like other means, there is also a way of weighting such as weighted average (weighting with degree difference in a characteristic part). This is as follows. For example, when a valve manufactured by another company is a target, if a sudden change in the specifications of a ball seat due to some technical reason causes a switch to another ball seat, since each ball seat has its unique angular velocity , the valves themselves have a large fluctuation in width with respect to the existing reference data in most of the open / close section fully close to fully open. When a similar trend continuously appears in a plurality of valves, the product data is weighted, and the reference data is written gradually with a fluctuation ratio smaller than the fluctuation width (for example, if the output data fluctuates from that of the previous reference data by 10%, gradually rewriting is carried out with a fluctuation ratio of 2%). This allows generation of reference data from the output data (measurement data) even if the reference data is not stored in advance, facilitating the achievement of a failure prediction system and an improvement in prediction accuracy.
    [0507] In this way, when baseline data is generated, by combining a process to generate and recently set baseline data and a process to rewrite existing baseline data as being leveled and weighted, product baseline data can be generated prior to production. product shipment, baseline data can be automatically generated by entering measurement data of a product manufactured by another company in the market, and various situations such as a sudden change in the use of a component in the market can be addressed.
    [0508] Thus, with the gyro sensor unit 1 described above used for the valve 3 during use, from the measurement data acquired by measurement by this gyro sensor unit 1, it is possible to perform a process to generate second reference data including the output data and product data according to valve open / close count 3. This second reference data generation process includes, as shown in Figure 34, a new reference data generation mode and a reference data change mode.
    [0510] Furthermore, in a plumbing system in which a plurality of valves are placed under maintenance at predetermined intervals, it is possible to perform a plumbing system maintenance method to perform, for each of the plurality of valves, prediction of a failure timing for each individual valve when using the valve status capture system of the present invention to acquire each prediction result, and exclude, from a maintenance target, a valve in which this prediction result exceeds the range.
    [0512] Note that Figure 35 and Figure 36 are graphs acquired by measuring a rotational movement by an acceleration sensor instead of the gyro sensor 7 under the same conditions as those represented in the other examples (Figure 25 to Figure 30). This acceleration sensor is connected, but not shown, to a position on the rear surface side of the coupling 5 of the monitoring unit 1 for measuring acceleration in three XYZ axes in Figure 1. The measurement is made at a position with approximately the same amount of movement as that of the gyro sensor 7 built into the monitoring unit 1.
    [0514] In Figure 35, acceleration is measured under conditions similar to those of Figure 25 to Figure 27. Figure 35 (a) is a graph of acceleration in the X-axis direction, Figure 35 (b) is a graph of acceleration in the Y-axis direction, and Figure 35 (c) is a graph of acceleration data in the Z-axis direction. The same is for Figure 36, and acceleration is measured under conditions similar to that of Figure 28 to Figure 30. Figure 36 (a) is an acceleration graph in the X-axis direction, Figure 36 (b) is an acceleration graph in the Y-axis direction, and Figure 36 (c) is a graph of acceleration data in the Z-axis direction. Also, while the graph markings are similar to those in the other drawings, the right vertical axis in Figure 35 and Figure 36 represent acceleration, and both have extremely small increments. (0.005 G to 0.02 G, G is the acceleration of gravity).
    [0516] As can be found from Figure 35 and Figure 36, for acceleration in any of three axis directions, only a pattern that fluctuates randomly in an extremely small interval can be acquired. Although a peak-like salient pattern is partially measured, this is merely a pattern that appears only after setting an extremely small acceleration scale, and it cannot be said that that measurement is not at a level of acquiring a graph pattern with practical precision for valve diagnosis. Thus, it has been confirmed that, although the acceleration sensor is an inertial sensor of the same type as that of the gyro sensor, the rotational movement of the valve cannot be captured solely by the acceleration sensor with the necessary precision.
    [0518] While the embodiments of the present invention have been described in detail above, the present invention is not limited to the description of the above embodiments, and they can be varied variously in a range that does not deviate from the above. essence of the invention described in the scope of the patent claim of the present invention.
    [0519] List of reference signs
    [0521] 1 monitoring unit (sensor unit)
    [0523] 2 actuator
    [0524] 3 ball valve (rotary valve)
    [0525] 4 control shaft (rotary shaft, valve stem)
    [0526] 7 gyro sensor
    [0527] 14 output shaft (rotary shaft, valve stem)
    [0528] 15 stem (rotary shaft, valve stem)
    [0529] 26th, 27th, 30th flow path
    [0530] 30 ball (valve body)
    [0531] 41 cloud server
    [0532] 42 Database
    [0533] A1, A2 ball seat (valve seat) (wear component) B rod bearing (wear component)
    [0534] C gland (wear component)
    [0535] T 1 , T 2 , T 3 trait value
    权利要求:
    Claims (7)
    [1]
    1. A valve state capture method to perform, based on angular velocity data of a valve stem opening and closing a valve, status monitoring of this valve, wherein the valve stem is pluggable and disconnectable a monitoring unit that has at least one semiconductor type gyro sensor and the angular velocity data includes a graph of the angular velocity acquired from this monitoring unit according to a rotational movement of the valve body from being fully open or fully closed to fully closed or fully open, the valve is a rotary valve that opens and closes or controls a flow path by rotating the valve stem and the valve stem is a rotary shaft formed of an output shaft and a control shaft of a valve automatic by means of the actuator or a stem of a manual valve by means of a manual handle, a vertical axis of the speed graph Angularity indicates angular velocity components in a direction substantially equal to the valve stem direction, the rotary valve is a quarter-turn ball valve or a butterfly valve, the state monitoring is at least one state capture of a valve seat, a valve stem rotation angle can be further calculated from the angular velocity data, and by associating a unique structure for the rotary valve with positions, sizes, and peak width of a plurality of peaks appearing on the angular velocity graph, an increase or decrease in rotational motion friction force between the valve body and the valve seat is estimated.
    [2]
    2. A valve status capture system comprising a valve, a sensor unit attached to this valve, and a server communicatively connected to this sensor unit and including a database, where the system is configured to capture a wear state of a wear component based on a trait value included in measurement data measured by a sensor included in the sensor unit of a valve stem that opens and closes the valve, the sensor is a gyro sensor that measures , such as measurement data, data of angular velocity with which the valve stem rotates, the database has stored therein a first reference data table having a plurality of pieces of label data and the trait data According to a predetermined count of valve openings / closings for each specific condition, the sensor unit and / or the server are provided with first means of fault diagnosis configured to capture the e state of wear and perform a valve fault diagnosis, and these first fault diagnosis means include specific data generation means that generate specific data having a specific valve condition, valve open / close count, and specific feature data based on angular velocity data, and data acquisition means that they acquire from the first reference data table first reference data having a specific trait value substantially equal to the specific trait value of the specific data.
    [3]
    3. A valve status capture system comprising a valve, a sensor unit attached to this valve, and a server communicatively connected to this sensor unit and including a database, wherein the system is configured to capture a wear state of a wear component based on a trait value included in measurement data measured by a sensor included in the sensor unit of a valve stem that opens and closes the valve, the sensor is a gyro sensor that measures , such as measurement data, data of angular velocity with which the valve stem rotates, the database has stored in it a learning model that calculates a piece of label data inferred from the trait data, the unit of sensor and / or the server are provided with second fault diagnosis means configured to detect the state of wear and perform a valve fault diagnosis, and these second fault diagnosis means include trait value generating means that generates the trait data based on the measurement data, inferred tag data calculation means that computes a piece of inferred tag data by means of the learning model based on the data trait, and comparing and determining means comparing this inferred tag data and a predetermined threshold for acquiring a determination result.
    [4]
    4. A valve status capture system comprising a valve, a sensor unit attached to this valve, and a server communicatively connected to this sensor unit and including a database, wherein the system is configured to capture a wear state of a wear component based on a trait value included in measurement data measured by a sensor included in the sensor unit of a valve stem that opens and closes the valve, the sensor is a gyro sensor that measures , such as measurement data, data of angular velocity with which the valve stem rotates, the database has stored in it a learning model that calculates model data from accumulated trait data, the sensor unit and / or The server is provided with third fault diagnosis means configured to capture the state of wear and perform a fault diagnosis of the valve, and these third fault diagnosis means include means from trait value generation generating predetermined trait data based on the measurement data, data accumulation means accumulating the trait data in the database and generating the accumulated trait data, data control means performing control default, model data calculation means that calculate the model data by means of the learning model on the basis of the accumulated trait data, index calculation means that calculate a predetermined index of the model data, and new training data. trait, and comparing and determining means comparing the index and a predetermined threshold to acquire a determination result.
    [5]
    The valve status sensing system according to any one of claims 2 to 4, wherein the wear component is a valve seat, the valve is a rotary valve, the sensor unit is a single unit capable of communication wireless with the server and including a power supply, and this sensor unit is attached pluggable and detachable in a mode capable of simultaneous rotation with the valve stem.
    [6]
    The valve condition sensing system according to any one of claims 2 to 5, wherein the label data is formed from dimensional data formed from one dimension of the wear component in a wear-free condition and / or quantity data Leakage formed from an amount of leakage when the valve is fully closed.
    [7]
    7. A valve status capture system comprising a valve, a sensor unit using a motion sensor attached to this valve, and a server communicatively connected to this sensor unit and including a database, wherein , this database has stored in it a second reference data table that includes output data and product data according to a count of valve openings / closings, the sensor unit and / or the server are provided with rooms Anomaly diagnosis means configured to detect a state of wear of a wear component included in the valve and to perform an anomaly diagnosis of the valve, these fourth anomaly diagnosis means include data generation means that generate measurement data that include output data and product data measured by the sensor unit based on a valve open / close count, acquiring data acquisition means, from the second a reference data table, second reference data having output data substantially equal to the valve output data included in this measurement data, and failure determination means determining prediction of Valve failures based on valve usage frequency data included in this second acquired reference data.
    类似技术:
    公开号 | 公开日 | 专利标题
    ES2813248A2|2021-03-22|Valve state monitoring system
    US10302454B2|2019-05-28|Retrofit device and method of retrofitting a flow meter
    US7836760B2|2010-11-23|Method and device for the assessment of fluid collection networks
    US20210310582A1|2021-10-07|Method for determining the degree of wear of a valve, and apparatus for carrying out said method
    JP5214386B2|2013-06-19|Motorized valve status monitoring and diagnosis apparatus and method
    US11174965B2|2021-11-16|Detecting maintenance statuses of valves
    ES2537962T3|2015-06-16|Electrohydraulic pressing apparatus for joining work pieces and method for performing a technical diagnosis of the pressing apparatus
    ES2809553T3|2021-03-04|System for the predictive maintenance of valves and procedure to carry out said maintenance
    CN106197759B|2019-07-02|A kind of temperature sensor control system
    US10837814B1|2020-11-17|Smart gas cylinder cap
    US11236843B2|2022-02-01|Monitoring an operating state of a valve
    JP2008033398A|2008-02-14|Apparatus and method for reading rotary meter
    CA3044175A1|2020-11-24|Non-invasive wireless remote monitoring method| for measuring, predicting and quantifying valve position, travel, cavitation, flashing, erosion, leakage and mechanical failure
    JP6802025B2|2020-12-16|Valve operation monitoring method and valve operation abnormality sign detection method
    JP6420654B2|2018-11-07|Steam trap float motion detection system
    Chraim et al.2013|Wireless valve position monitoring: A MEMS approach
    JP2003083849A|2003-03-19|Diagnostic system
    KR102363953B1|2022-02-17|Apparatus for displaying opening degree of valve and system for monitoring opening degree of valve
    JP6957686B2|2021-11-02|Status recorder for automatic valve
    JP2019100442A|2019-06-24|Diagnosis system for pneumatic operation valve and diagnosis method for pneumatic operation valve
    BR102016024422A2|2018-05-02|ELECTRONIC DEVICE FOR INTELLIGENT VALVE MONITORING AND CONTROL
    TWM449264U|2013-03-21|Pressure gauge with improved reed type sensing device
    KR200450646Y1|2010-10-20|Sensor fixtures for measuring mechanical water meters
    JP2005345427A|2005-12-15|Measuring device of flow rate
    BR112012027910B1|2021-10-05|CONTROL VALVE DIAGNOSIS
    同族专利:
    公开号 | 公开日
    ES2813248R1|2021-04-14|
    DE112019002316T5|2021-02-18|
    CN112469937A|2021-03-09|
    WO2019235599A1|2019-12-12|
    JPWO2019235599A1|2021-08-05|
    US20210123543A1|2021-04-29|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US5487302A|1993-03-01|1996-01-30|Lockheed Martin Energy Systems, Inc.|Method and system for measuring gate valve clearances and seating force|
    US7886766B2|2006-12-27|2011-02-15|Eltav Wireless Monitoring Ltd.|Device and system for monitoring valves|
    DE102008064359A1|2008-12-22|2010-07-01|Abb Technology Ag|Method for the position-dependent determination of electronic wear status of a valve mechanism and pneumatic valve|
    DE102009022891B3|2009-05-27|2010-11-18|Abb Technology Ag|Method for electronic wear state determination in a valve arrangement|
    JP4990338B2|2009-10-13|2012-08-01|岡野バルブ製造株式会社|Soundness diagnosis method, soundness diagnosis device and program for electric valve device|
    JP4843111B1|2011-05-18|2011-12-21|住友精化株式会社|Maintenance method of automatic open / close valve|
    IL227260A|2013-06-30|2017-01-31|Radomsky Israel|Device and system for wirelessly controlling and monitoring of quarter turn valves|
    JP6221652B2|2013-11-08|2017-11-01|セイコーエプソン株式会社|Life prediction method, life prediction device, life prediction system, life calculation device, and rotating machine|
    CN204284634U|2014-11-03|2015-04-22|安徽翰翔仪器设备有限公司|A kind of valve opening degree accurate detection device|
    US9934671B1|2016-10-24|2018-04-03|Fisher Controls International Llc|Valve service detection through data analysis|
    US10619760B2|2016-10-24|2020-04-14|Fisher Controls International Llc|Time-series analytics for control valve health assessment|JP6779456B1|2020-03-16|2020-11-04|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6783486B1|2020-03-17|2020-11-11|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6783488B1|2020-03-27|2020-11-11|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6783489B1|2020-03-27|2020-11-11|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6779457B1|2020-04-15|2020-11-04|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6779459B1|2020-04-28|2020-11-04|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    JP6779458B1|2020-04-28|2020-11-04|金子産業株式会社|Machine learning equipment, data processing systems, inference equipment and machine learning methods|
    CN112197056B|2020-10-19|2021-07-20|台州科创科技信息咨询有限公司|Mechanical ball valve service life detector|
    法律状态:
    2021-03-22| BA2A| Patent application published|Ref document number: 2813248 Country of ref document: ES Kind code of ref document: A2 Effective date: 20210322 |
    2021-04-14| EC2A| Search report published|Ref document number: 2813248 Country of ref document: ES Kind code of ref document: R1 Effective date: 20210407 |
    优先权:
    申请号 | 申请日 | 专利标题
    JP2018109083|2018-06-06|
    PCT/JP2019/022649|WO2019235599A1|2018-06-06|2019-06-06|Valve state monitoring system|
    [返回顶部]